# QuickPLS 2.62.1 method tutorials

Status: detailed numbered procedures for all 41 supported method entries, five explicit unavailable CB-SEM capability cells, reproducible sample mappings, and screenshots from the qualified 2.62.1 binary are included.

## The common eight-step workflow

Every supported method follows the same main path. Method-specific choices are listed in the next section.

1. On **Home**, choose **Sample Projects** for a ready example, **New Project** for your own work, or **Open Project** for an existing `.qpls` file.

   ![Open a bundled sample project](screenshots/01-open-bundled-sample.png)

2. If you are using your own file, open **Data**, choose **Import Data**, select the file and data representation, review the preview, and choose **Import**. QuickPLS creates a dataset version; it does not overwrite the source file.

   ![Choose the data source](screenshots/02-import-data-source.png)

   ![Review the parsed data preview](screenshots/03-import-data-preview.png)

3. For SEM methods, open **Model**, create or select a model, assign indicators, add the required paths, groups, interactions, or higher-order construct, and resolve **Model Issues**. PCA, NCA, and ordinary regression can work directly with imported columns.

   ![Author a model on the canvas](screenshots/04-author-model.png)

4. Choose **Calculate**. In **Find a method**, type the method name or alias. Select the result row. Combined rows now show their modes directly—for example, Regression shows **OLS · Logistic · Bootstrap · PROCESS**.

   ![Find and select a calculation method](screenshots/07-hoc-calculation-setup.png)

5. Complete the visible required settings. Essential inputs appear first. Open **Advanced settings** only for iteration or specialist controls, and open **Method Details** for assumptions and scope.

   The selected method stays at the top of the same calculation screen; required settings are in the centre and specialist settings remain collapsed until requested.

6. Read **Readiness**. Select the named correction when a blocker appears. Warnings are informative and do not disable a valid run.

   In the screenshot above, the footer says **Ready to calculate**. If the model or data is not ready, this position contains the exact correction instead.

7. Leave **Open Results when finished** selected and choose **Start calculation** in the fixed footer. A saved writable project runs without another Save As dialog. An unsaved or read-only project asks for one writable destination and then continues automatically.

   The **Start calculation** button remains in the bottom-right footer even when the settings area scrolls.

8. In **Results**, use the left output tree for tables and charts. Use the top contextual toolbar for supported diagram values. Choose **Save Report** to retain the exact result and **Export** for CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON where offered.

   ![Read the PLS results tree and table](screenshots/05-pls-results.png)

   ![Review the completed export receipt](screenshots/06-export-complete.png)

## Method-specific screenshot examples

The common eight-step sequence does not change between methods. The examples below show the setup and Results variations that users will encounter after choosing the relevant method.

| Method family | Setup | Results |
|---|---|---|
| Higher-order PLS | [Calculation setup](screenshots/07-hoc-calculation-setup.png) | [Higher-order output](screenshots/08-hoc-results.png) |
| PLS Model Fit | Uses the ordinary PLS calculation setup | [Fit tables and full result tree](screenshots/09-pls-model-fit-results.png) |
| Fixed-score nonlinear diagnostics | [Nonlinear setup](screenshots/10-nonlinear-setup.png) | [Nonlinear results](screenshots/11-nonlinear-results.png) |
| Authored quadratic relationship | Uses the PLS calculation setup after authoring the relationship | [Quadratic relationship results](screenshots/12-authored-quadratic-results.png) |
| Gaussian-copula endogeneity | [Select focal paths](screenshots/13-endogeneity-setup.png) | [Endogeneity results](screenshots/14-endogeneity-results.png) |
| PLS model comparison | [Choose compatible models](screenshots/15-model-comparison-setup.png) | [Comparison result](screenshots/16-model-comparison-results.png) |
| Prediction-oriented model selection | [Choose candidate models](screenshots/17-prediction-selection-setup.png) | [Candidate ranking](screenshots/18-prediction-selection-results.png) |
| MICOM / MGA | [MGA setup](screenshots/19-mga-setup.png) | [MGA results](screenshots/20-mga-results.png) |
| PLS-POS | [Segmentation setup](screenshots/21-pls-pos-setup.png) | [PLS-POS results](screenshots/22-pls-pos-results.png) |

The PLS Model Fit example below shows how method-specific tables remain in the same Results tree used by the common workflow:

![Inspect PLS Model Fit tables in Results](screenshots/09-pls-model-fit-results.png)

## Method-by-method route and expected result

The “Calculate choice” text below is the exact row or mode a user selects. “First output” is the practical place to begin interpretation; every additional applicable output remains in the Results tree.

| Method | Calculate choice and required setup | Suggested practice data/project | First output to inspect |
|---|---|---|---|
| PLS-SEM Algorithm | **PLS-SEM Algorithm**; an acyclic SEM model with indicators and at least one structural path. Weighting and result-data choices are visible; iteration controls are under **Advanced settings**. | **Simple Reflective PLS-SEM** or **Corporate Reputation** | Graphical Output, path coefficients, outer model, R-square, reliability/validity, fit and model/data tables |
| PLS power analysis | **Post-hoc Technical Minimum Sample Size** for a completed significant bootstrap path, or **PLS-SEM Sample Size and Power** for the prospective two-construct design. | Simple reflective model plus its bootstrap result; the prospective setup supplies its own grid | Minimum sample-size decision or power curve and simulation accounting |
| Weighted PLS | **Weighted PLS**; choose one positive numeric case-weight variable. | Packaged `samples/weighted-pls.csv`; use `case_wt` as the weight | Weighted estimates, weighting/accounting evidence and the result diagram |
| Consistent PLS | **Consistent PLS**; use eligible reflective measurement blocks. | **Simple Reflective PLS-SEM** | Corrected structural and measurement estimates plus quality/fit tables |
| Principal Component Analysis | **Principal Component Analysis**; select numeric variables and a retention rule. | **Corporate Reputation** numeric indicators | Explained/cumulative variance, scree plot, loadings and scores |
| PLS-SEM Bootstrapping | **PLS-SEM Bootstrapping**; choose draws, confidence level, tail/interval options when available, seed and workers. | **Simple Reflective PLS-SEM** or **Corporate Reputation** | Direct-path inference, effects, outer-model inference and replicate receipt |
| PLSc Consistent Bootstrapping | **PLSc Consistent Bootstrapping**; reflective model and valid PLSc point fit. | **Simple Reflective PLS-SEM** | PLSc bootstrap estimates, intervals, probabilities and replicate accounting |
| Blindfolding | **Blindfolding (Q²)**; reflective endogenous constructs and a valid omission distance. | **Simple Reflective PLS-SEM** | Cross-validated redundancy Q² table |
| Permutation / Structural Path Randomization | **Structural Path Randomization** for the single-model Freedman-Lane test; use the group workflow for MICOM permutation MGA. | Packaged `samples/group-pls.csv`; use `group` as the group column | Randomized structural-path probability or group permutation tables |
| PLSc Consistent Permutation | **PLSc Consistent Permutation**; select the two predefined groups and qualified reflective PLSc profile. | Packaged `samples/group-pls.csv` | Group differences, directional probabilities and assignment accounting |
| CVPAT | **PLSpredict / CVPAT**; use an eligible PLS model and seed. The cross-validation plan is displayed. | **Corporate Reputation** | CVPAT benchmark comparison and prediction-error chart |
| Confirmatory Composite Analysis | **CCA composite residual diagnostics**; eligible composite model. | **Corporate Reputation** | Residual summary, observed/reproduced correlations and residual chart |
| Confirmatory Tetrad Analysis | **Confirmatory Tetrad Analysis**; at least one ordinary construct with four indicators. | Packaged `samples/cta-pls.csv`; assign `x1` to `x4` to one construct | Descriptive tetrads and eligible-block accounting; inferential classification remains explicitly unavailable |
| HTMT / HTMT+ | **Discriminant Validity — HTMT/HTMT+**; at least two eligible multi-indicator reflective constructs. Choose point matrices or fixed bootstrap inference. | **Organizational Identification Model** | HTMT+ and signed HTMT matrices/heatmaps, then optional interval output |
| Global GoF | **Global Goodness of Fit**; a PLS result with applicable reflective AVE and endogenous R-square. | **Simple Reflective PLS-SEM** | Legacy descriptive GoF value and its interpretation warning |
| PLS Model Fit | Run **PLS-SEM Algorithm**; Model Fit is produced automatically for an eligible point result. | **Corporate Reputation** | Model Fit summary and details tables |
| PLS Model Comparison | **PLS Model Comparison**; select two compatible saved ordinary-PLS models sharing the required data and fold design. | **Organizational Identification Model**; create a model variant in the same project | Overview, predictive loss, paired CVPAT, BIC and decision evidence |
| Prediction-Oriented Model Selection | **Prediction-Oriented Model Selection**; select 2–20 compatible saved PLS models. | Packaged `samples/model-selection-three-candidate.qpls` | Candidate ranking, equation BIC, ties/mixed evidence and decision table |
| MICOM | **MICOM and Multigroup Analysis (PLS / PLSc)**; choose groups, confirm configural setup and enable MICOM. | Packaged `samples/group-pls.csv` or **Organizational Identification Model** using `gender` | Configural/compositional invariance and equality-of-means/variances steps |
| PLS-MGA | Same shared **MICOM and Multigroup Analysis** row; select the ordinary PLS profile and requested MGA procedures. | Group fixture above | Group estimates, pairwise/omnibus differences, intervals, probabilities and multiplicity |
| PLSc-MGA | Same shared row; select the reflective PLSc profile. | Group fixture with reflective blocks | Consistent group estimates, MICOM gate and PLSc-MGA comparison tables |
| PLSpredict | **PLSpredict / CVPAT**; select an eligible model and seed. | **Corporate Reputation** | Indicator prediction errors against IA/LM benchmarks and RMSE comparison chart |
| PLS-POS | Open the shared MultiMod calculation workspace and choose **PLS-POS**; select K/profile and start settings. | **Organizational Identification Model** | Objective/search history, assignments, membership, segment estimates and stability charts |
| FIMIX-PLS | Shared MultiMod workspace, **FIMIX-PLS**; choose the bounded segment plan. | **Organizational Identification Model** | Candidate criteria, likelihood history, posterior membership, assignments and segment shares |
| IPMA | **Importance-Performance Map Analysis**; choose one endogenous target. | **Corporate Reputation** | Construct importance/performance map and construct/indicator tables |
| Moderation | Use the authored moderation model and its **PLS-SEM conditional process** route; select point or supported bootstrap profile. | **Organizational Identification - Two-Outcome Moderation** | Interaction coefficients, probes, simple slopes, conditional effects and plots |
| Mediation | Run PLS for point effects or **PLS-SEM Bootstrapping** for inference; the model needs the required indirect path. | **Mediation** or **Organizational Identification - Mediation** | Direct, specific indirect, aggregate indirect and total effects |
| Nonlinear relationships | **Quadratic Nonlinear Effects**; author a quadratic effect on a structural path for the full route, then choose point/percentile/BCa inference. | Corporate Reputation plus an authored quadratic path | Joint linear/quadratic coefficients, incremental R-square, curve, slopes and turning point |
| Higher-order models | Author a supported HOC in **Model**, then use the General SEM/PLS route and select point or bootstrap. | **Organizational Identification - Higher-Order** | Stage-one/stage-two receipts, structural paths, HOC weights/loadings and inference when requested |
| Gaussian-copula endogeneity | **Gaussian-Copula Endogeneity Diagnostics**; tick the focal structural paths. | Packaged `samples/endogeneity.csv` | Source-normality, joint/sensitivity fits, copula terms and multiplicity-adjusted probabilities |
| GSCA | **GSCA**; eligible component model with reflective or formative blocks and recursive paths. | Packaged `samples/observed-methods.csv` | Fit summary, component weights/loadings, structural estimates and residual/fit chart |
| Binary logistic regression | **Regression**, then **Binary logistic**; select a strict 0/1 outcome and non-overlapping predictors/controls. | Packaged `samples/observed-methods.csv`; use `bin_y` as outcome | Coefficients/odds ratios, fit, classification/confusion, ROC/AUC and cutoff chart |
| Necessary Condition Analysis | **Necessary Condition Analysis**; choose different numeric X and Y variables, ceiling line and permutations. | Packaged `samples/observed-methods.csv` | Ceiling/effect-size, bottleneck table, permutation inference and ceiling plot |
| PROCESS/path analysis | **Regression**, then **Graph-defined Path Analysis / PROCESS**; author the displayed observed-variable graph and probes. | Packaged `samples/process-path-analysis.csv` | Equation coefficients, direct/indirect effects, conditional effects, simple slopes and Johnson-Neyman output |
| PROCESS bootstrapping | Same PROCESS setup, then enable **Case-resampling bootstrap** and choose draws/seed. | PROCESS fixture above | Bootstrap effects, intervals, failure accounting and supported conditional results |
| OLS regression | **Regression**, then **Ordinary least squares**; choose outcome, predictors and optional controls. | Packaged `samples/observed-methods.csv` | Model/ANOVA/coefficients, diagnostics, predictions/residuals and five diagnostic charts |
| Regression bootstrapping | OLS or Logistic setup, enable **Case-resampling bootstrap**, then set samples/workers/seed. | Corresponding observed-variable fixture | Bootstrap coefficient/effect intervals and replicate accounting |
| CB-SEM | **CB-SEM / CFA**, choose the recursive CB-SEM point mode; use raw continuous data and a qualified common-factor model. | Packaged `samples/recursive-cbsem.csv` | Fit indices, parameter estimates, standardized solution, residuals and diagram |
| CB-SEM bootstrapping | Same shared row, enable exact case bootstrap and choose supported draws/inference. | CB-SEM fixture above | Point fit plus parameter bootstrap estimates, intervals, probabilities and replicate receipt |
| CFA | **CB-SEM / CFA**, choose CFA point mode; reflective common-factor model with no structural regressions. | Packaged `samples/two-factor-cfa.csv` | Fit summary, loadings, variances/covariances, standardized solution and residuals |
| PCA for CB-SEM preparation | **Principal Component Analysis**; this is exploratory data reduction and does not replace CFA. | CFA fixture numeric columns | Scree, variance, loadings and scores |


<!-- generated-method-tutorials:start -->

## Detailed numbered tutorial for every supported method

The procedures below deliberately repeat the exact buttons and handoff steps. A user can open the relevant method heading and complete the workflow without having to combine instructions from different sections.

### 1. PLS-SEM Algorithm

**Use and preparation.** **PLS-SEM Algorithm**; an acyclic SEM model with indicators and at least one structural path. Weighting and result-data choices are visible; iteration controls are under **Advanced settings**.

**Practice material.** **Simple Reflective PLS-SEM** or **Corporate Reputation**

**Begin interpretation with.** Graphical Output, path coefficients, outer model, R-square, reliability/validity, fit and model/data tables

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Simple Reflective PLS-SEM or Corporate Reputation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Graphical Output, path coefficients, outer model, R-square, reliability/validity, fit and model/data tables
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLS-SEM Algorithm preparation or calculation context](screenshots/04-author-model.png)

![PLS-SEM Algorithm Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 2. PLS power analysis

**Use and preparation.** **Post-hoc Technical Minimum Sample Size** for a completed significant bootstrap path, or **PLS-SEM Sample Size and Power** for the prospective two-construct design.

**Practice material.** Simple reflective model plus its bootstrap result; the prospective setup supplies its own grid

**Begin interpretation with.** Minimum sample-size decision or power curve and simulation accounting

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Simple reflective model plus its bootstrap result; the prospective setup supplies its own grid**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Minimum sample-size decision or power curve and simulation accounting
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLS power analysis preparation or calculation context](screenshots/04-author-model.png)

![PLS power analysis Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 3. Weighted PLS

**Use and preparation.** **Weighted PLS**; choose one positive numeric case-weight variable.

**Practice material.** Packaged `samples/weighted-pls.csv`; use `case_wt` as the weight

**Begin interpretation with.** Weighted estimates, weighting/accounting evidence and the result diagram

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/weighted-pls.csv`; use `case_wt` as the weight**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Weighted estimates, weighting/accounting evidence and the result diagram
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Weighted PLS preparation or calculation context](screenshots/04-author-model.png)

![Weighted PLS Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 4. Consistent PLS

**Use and preparation.** **Consistent PLS**; use eligible reflective measurement blocks.

**Practice material.** **Simple Reflective PLS-SEM**

**Begin interpretation with.** Corrected structural and measurement estimates plus quality/fit tables

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Simple Reflective PLS-SEM**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Corrected structural and measurement estimates plus quality/fit tables
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Consistent PLS preparation or calculation context](screenshots/04-author-model.png)

![Consistent PLS Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 5. Principal Component Analysis

**Use and preparation.** **Principal Component Analysis**; select numeric variables and a retention rule.

**Practice material.** **Corporate Reputation** numeric indicators

**Begin interpretation with.** Explained/cumulative variance, scree plot, loadings and scores

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Corporate Reputation numeric indicators**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Explained/cumulative variance, scree plot, loadings and scores
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Principal Component Analysis preparation or calculation context](screenshots/04-author-model.png)

![Principal Component Analysis Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 6. PLS-SEM Bootstrapping

**Use and preparation.** **PLS-SEM Bootstrapping**; choose draws, confidence level, tail/interval options when available, seed and workers.

**Practice material.** **Simple Reflective PLS-SEM** or **Corporate Reputation**

**Begin interpretation with.** Direct-path inference, effects, outer-model inference and replicate receipt

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Simple Reflective PLS-SEM or Corporate Reputation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Direct-path inference, effects, outer-model inference and replicate receipt
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLS-SEM Bootstrapping preparation or calculation context](screenshots/04-author-model.png)

![PLS-SEM Bootstrapping Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 7. PLSc Consistent Bootstrapping

**Use and preparation.** **PLSc Consistent Bootstrapping**; reflective model and valid PLSc point fit.

**Practice material.** **Simple Reflective PLS-SEM**

**Begin interpretation with.** PLSc bootstrap estimates, intervals, probabilities and replicate accounting

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Simple Reflective PLS-SEM**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: PLSc bootstrap estimates, intervals, probabilities and replicate accounting
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLSc Consistent Bootstrapping preparation or calculation context](screenshots/04-author-model.png)

![PLSc Consistent Bootstrapping Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 8. Blindfolding

**Use and preparation.** **Blindfolding (Q²)**; reflective endogenous constructs and a valid omission distance.

**Practice material.** **Simple Reflective PLS-SEM**

**Begin interpretation with.** Cross-validated redundancy Q² table

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Simple Reflective PLS-SEM**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Cross-validated redundancy Q² table
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Blindfolding preparation or calculation context](screenshots/04-author-model.png)

![Blindfolding Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 9. Permutation / Structural Path Randomization

**Use and preparation.** **Structural Path Randomization** for the single-model Freedman-Lane test; use the group workflow for MICOM permutation MGA.

**Practice material.** Packaged `samples/group-pls.csv`; use `group` as the group column

**Begin interpretation with.** Randomized structural-path probability or group permutation tables

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/group-pls.csv`; use `group` as the group column**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Randomized structural-path probability or group permutation tables
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Permutation / Structural Path Randomization preparation or calculation context](screenshots/04-author-model.png)

![Permutation / Structural Path Randomization Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 10. PLSc Consistent Permutation

**Use and preparation.** **PLSc Consistent Permutation**; select the two predefined groups and qualified reflective PLSc profile.

**Practice material.** Packaged `samples/group-pls.csv`

**Begin interpretation with.** Group differences, directional probabilities and assignment accounting

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/group-pls.csv`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Group differences, directional probabilities and assignment accounting
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLSc Consistent Permutation preparation or calculation context](screenshots/04-author-model.png)

![PLSc Consistent Permutation Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 11. CVPAT

**Use and preparation.** **PLSpredict / CVPAT**; use an eligible PLS model and seed. The cross-validation plan is displayed.

**Practice material.** **Corporate Reputation**

**Begin interpretation with.** CVPAT benchmark comparison and prediction-error chart

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Corporate Reputation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: CVPAT benchmark comparison and prediction-error chart
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![CVPAT preparation or calculation context](screenshots/04-author-model.png)

![CVPAT Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 12. Confirmatory Composite Analysis

**Use and preparation.** **CCA composite residual diagnostics**; eligible composite model.

**Practice material.** **Corporate Reputation**

**Begin interpretation with.** Residual summary, observed/reproduced correlations and residual chart

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Corporate Reputation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Residual summary, observed/reproduced correlations and residual chart
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Confirmatory Composite Analysis preparation or calculation context](screenshots/04-author-model.png)

![Confirmatory Composite Analysis Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 13. Confirmatory Tetrad Analysis

**Use and preparation.** **Confirmatory Tetrad Analysis**; at least one ordinary construct with four indicators.

**Practice material.** Packaged `samples/cta-pls.csv`; assign `x1` to `x4` to one construct

**Begin interpretation with.** Descriptive tetrads and eligible-block accounting; inferential classification remains explicitly unavailable

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/cta-pls.csv`; assign `x1` to `x4` to one construct**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Descriptive tetrads and eligible-block accounting; inferential classification remains explicitly unavailable
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Confirmatory Tetrad Analysis preparation or calculation context](screenshots/04-author-model.png)

![Confirmatory Tetrad Analysis Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 14. HTMT / HTMT+

**Use and preparation.** **Discriminant Validity — HTMT/HTMT+**; at least two eligible multi-indicator reflective constructs. Choose point matrices or fixed bootstrap inference.

**Practice material.** **Organizational Identification Model**

**Begin interpretation with.** HTMT+ and signed HTMT matrices/heatmaps, then optional interval output

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Organizational Identification Model**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: HTMT+ and signed HTMT matrices/heatmaps, then optional interval output
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![HTMT / HTMT+ preparation or calculation context](screenshots/04-author-model.png)

![HTMT / HTMT+ Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 15. Global GoF

**Use and preparation.** **Global Goodness of Fit**; a PLS result with applicable reflective AVE and endogenous R-square.

**Practice material.** **Simple Reflective PLS-SEM**

**Begin interpretation with.** Legacy descriptive GoF value and its interpretation warning

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Simple Reflective PLS-SEM**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Legacy descriptive GoF value and its interpretation warning
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Global GoF preparation or calculation context](screenshots/04-author-model.png)

![Global GoF Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 16. PLS Model Fit

**Use and preparation.** Run **PLS-SEM Algorithm**; Model Fit is produced automatically for an eligible point result.

**Practice material.** **Corporate Reputation**

**Begin interpretation with.** Model Fit summary and details tables

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Corporate Reputation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Model Fit summary and details tables
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLS Model Fit preparation or calculation context](screenshots/07-hoc-calculation-setup.png)

![PLS Model Fit Results context](screenshots/09-pls-model-fit-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 17. PLS Model Comparison

**Use and preparation.** **PLS Model Comparison**; select two compatible saved ordinary-PLS models sharing the required data and fold design.

**Practice material.** **Organizational Identification Model**; create a model variant in the same project

**Begin interpretation with.** Overview, predictive loss, paired CVPAT, BIC and decision evidence

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Organizational Identification Model; create a model variant in the same project** from **Sample Projects** or select its `.qpls` file with **Open Project**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Overview, predictive loss, paired CVPAT, BIC and decision evidence
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLS Model Comparison preparation or calculation context](screenshots/15-model-comparison-setup.png)

![PLS Model Comparison Results context](screenshots/16-model-comparison-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 18. Prediction-Oriented Model Selection

**Use and preparation.** **Prediction-Oriented Model Selection**; select 2–20 compatible saved PLS models.

**Practice material.** Packaged `samples/model-selection-three-candidate.qpls`

**Begin interpretation with.** Candidate ranking, equation BIC, ties/mixed evidence and decision table

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Packaged `samples/model-selection-three-candidate.qpls`** from **Sample Projects** or select its `.qpls` file with **Open Project**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Candidate ranking, equation BIC, ties/mixed evidence and decision table
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Prediction-Oriented Model Selection preparation or calculation context](screenshots/17-prediction-selection-setup.png)

![Prediction-Oriented Model Selection Results context](screenshots/18-prediction-selection-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 19. MICOM

**Use and preparation.** **MICOM and Multigroup Analysis (PLS / PLSc)**; choose groups, confirm configural setup and enable MICOM.

**Practice material.** Packaged `samples/group-pls.csv` or **Organizational Identification Model** using `gender`

**Begin interpretation with.** Configural/compositional invariance and equality-of-means/variances steps

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/group-pls.csv` or Organizational Identification Model using `gender`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Configural/compositional invariance and equality-of-means/variances steps
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![MICOM preparation or calculation context](screenshots/19-mga-setup.png)

![MICOM Results context](screenshots/20-mga-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 20. PLS-MGA

**Use and preparation.** Same shared **MICOM and Multigroup Analysis** row; select the ordinary PLS profile and requested MGA procedures.

**Practice material.** Group fixture above

**Begin interpretation with.** Group estimates, pairwise/omnibus differences, intervals, probabilities and multiplicity

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Group fixture above**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Group estimates, pairwise/omnibus differences, intervals, probabilities and multiplicity
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLS-MGA preparation or calculation context](screenshots/19-mga-setup.png)

![PLS-MGA Results context](screenshots/20-mga-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 21. PLSc-MGA

**Use and preparation.** Same shared row; select the reflective PLSc profile.

**Practice material.** Group fixture with reflective blocks

**Begin interpretation with.** Consistent group estimates, MICOM gate and PLSc-MGA comparison tables

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Group fixture with reflective blocks**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Consistent group estimates, MICOM gate and PLSc-MGA comparison tables
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLSc-MGA preparation or calculation context](screenshots/19-mga-setup.png)

![PLSc-MGA Results context](screenshots/20-mga-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 22. PLSpredict

**Use and preparation.** **PLSpredict / CVPAT**; select an eligible model and seed.

**Practice material.** **Corporate Reputation**

**Begin interpretation with.** Indicator prediction errors against IA/LM benchmarks and RMSE comparison chart

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Corporate Reputation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Indicator prediction errors against IA/LM benchmarks and RMSE comparison chart
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLSpredict preparation or calculation context](screenshots/04-author-model.png)

![PLSpredict Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 23. PLS-POS

**Use and preparation.** Open the shared MultiMod calculation workspace and choose **PLS-POS**; select K/profile and start settings.

**Practice material.** **Organizational Identification Model**

**Begin interpretation with.** Objective/search history, assignments, membership, segment estimates and stability charts

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Organizational Identification Model**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Objective/search history, assignments, membership, segment estimates and stability charts
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PLS-POS preparation or calculation context](screenshots/21-pls-pos-setup.png)

![PLS-POS Results context](screenshots/22-pls-pos-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 24. FIMIX-PLS

**Use and preparation.** Shared MultiMod workspace, **FIMIX-PLS**; choose the bounded segment plan.

**Practice material.** **Organizational Identification Model**

**Begin interpretation with.** Candidate criteria, likelihood history, posterior membership, assignments and segment shares

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Organizational Identification Model**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Candidate criteria, likelihood history, posterior membership, assignments and segment shares
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![FIMIX-PLS preparation or calculation context](screenshots/04-author-model.png)

![FIMIX-PLS Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 25. IPMA

**Use and preparation.** **Importance-Performance Map Analysis**; choose one endogenous target.

**Practice material.** **Corporate Reputation**

**Begin interpretation with.** Construct importance/performance map and construct/indicator tables

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Corporate Reputation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Construct importance/performance map and construct/indicator tables
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![IPMA preparation or calculation context](screenshots/04-author-model.png)

![IPMA Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 26. Moderation

**Use and preparation.** Use the authored moderation model and its **PLS-SEM conditional process** route; select point or supported bootstrap profile.

**Practice material.** **Organizational Identification - Two-Outcome Moderation**

**Begin interpretation with.** Interaction coefficients, probes, simple slopes, conditional effects and plots

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Organizational Identification - Two-Outcome Moderation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Interaction coefficients, probes, simple slopes, conditional effects and plots
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Moderation preparation or calculation context](screenshots/04-author-model.png)

![Moderation Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 27. Mediation

**Use and preparation.** Run PLS for point effects or **PLS-SEM Bootstrapping** for inference; the model needs the required indirect path.

**Practice material.** **Mediation** or **Organizational Identification - Mediation**

**Begin interpretation with.** Direct, specific indirect, aggregate indirect and total effects

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Mediation or Organizational Identification - Mediation**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Direct, specific indirect, aggregate indirect and total effects
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Mediation preparation or calculation context](screenshots/04-author-model.png)

![Mediation Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 28. Nonlinear relationships

**Use and preparation.** **Quadratic Nonlinear Effects**; author a quadratic effect on a structural path for the full route, then choose point/percentile/BCa inference.

**Practice material.** Corporate Reputation plus an authored quadratic path

**Begin interpretation with.** Joint linear/quadratic coefficients, incremental R-square, curve, slopes and turning point

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Corporate Reputation plus an authored quadratic path**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Joint linear/quadratic coefficients, incremental R-square, curve, slopes and turning point
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Nonlinear relationships preparation or calculation context](screenshots/10-nonlinear-setup.png)

![Nonlinear relationships Results context](screenshots/11-nonlinear-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 29. Higher-order models

**Use and preparation.** Author a supported HOC in **Model**, then use the General SEM/PLS route and select point or bootstrap.

**Practice material.** **Organizational Identification - Higher-Order**

**Begin interpretation with.** Stage-one/stage-two receipts, structural paths, HOC weights/loadings and inference when requested

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Organizational Identification - Higher-Order**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Stage-one/stage-two receipts, structural paths, HOC weights/loadings and inference when requested
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Higher-order models preparation or calculation context](screenshots/07-hoc-calculation-setup.png)

![Higher-order models Results context](screenshots/08-hoc-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 30. Gaussian-copula endogeneity

**Use and preparation.** **Gaussian-Copula Endogeneity Diagnostics**; tick the focal structural paths.

**Practice material.** Packaged `samples/endogeneity.csv`

**Begin interpretation with.** Source-normality, joint/sensitivity fits, copula terms and multiplicity-adjusted probabilities

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/endogeneity.csv`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Source-normality, joint/sensitivity fits, copula terms and multiplicity-adjusted probabilities
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Gaussian-copula endogeneity preparation or calculation context](screenshots/13-endogeneity-setup.png)

![Gaussian-copula endogeneity Results context](screenshots/14-endogeneity-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 31. GSCA

**Use and preparation.** **GSCA**; eligible component model with reflective or formative blocks and recursive paths.

**Practice material.** Packaged `samples/observed-methods.csv`

**Begin interpretation with.** Fit summary, component weights/loadings, structural estimates and residual/fit chart

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/observed-methods.csv`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Fit summary, component weights/loadings, structural estimates and residual/fit chart
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![GSCA preparation or calculation context](screenshots/04-author-model.png)

![GSCA Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 32. Binary logistic regression

**Use and preparation.** **Regression**, then **Binary logistic**; select a strict 0/1 outcome and non-overlapping predictors/controls.

**Practice material.** Packaged `samples/observed-methods.csv`; use `bin_y` as outcome

**Begin interpretation with.** Coefficients/odds ratios, fit, classification/confusion, ROC/AUC and cutoff chart

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/observed-methods.csv`; use `bin_y` as outcome**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Coefficients/odds ratios, fit, classification/confusion, ROC/AUC and cutoff chart
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Binary logistic regression preparation or calculation context](screenshots/04-author-model.png)

![Binary logistic regression Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 33. Necessary Condition Analysis

**Use and preparation.** **Necessary Condition Analysis**; choose different numeric X and Y variables, ceiling line and permutations.

**Practice material.** Packaged `samples/observed-methods.csv`

**Begin interpretation with.** Ceiling/effect-size, bottleneck table, permutation inference and ceiling plot

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/observed-methods.csv`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Ceiling/effect-size, bottleneck table, permutation inference and ceiling plot
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Necessary Condition Analysis preparation or calculation context](screenshots/04-author-model.png)

![Necessary Condition Analysis Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 34. PROCESS/path analysis

**Use and preparation.** **Regression**, then **Graph-defined Path Analysis / PROCESS**; author the displayed observed-variable graph and probes.

**Practice material.** Packaged `samples/process-path-analysis.csv`

**Begin interpretation with.** Equation coefficients, direct/indirect effects, conditional effects, simple slopes and Johnson-Neyman output

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/process-path-analysis.csv`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Equation coefficients, direct/indirect effects, conditional effects, simple slopes and Johnson-Neyman output
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PROCESS/path analysis preparation or calculation context](screenshots/04-author-model.png)

![PROCESS/path analysis Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 35. PROCESS bootstrapping

**Use and preparation.** Same PROCESS setup, then enable **Case-resampling bootstrap** and choose draws/seed.

**Practice material.** PROCESS fixture above

**Begin interpretation with.** Bootstrap effects, intervals, failure accounting and supported conditional results

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **PROCESS fixture above**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Bootstrap effects, intervals, failure accounting and supported conditional results
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PROCESS bootstrapping preparation or calculation context](screenshots/04-author-model.png)

![PROCESS bootstrapping Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 36. OLS regression

**Use and preparation.** **Regression**, then **Ordinary least squares**; choose outcome, predictors and optional controls.

**Practice material.** Packaged `samples/observed-methods.csv`

**Begin interpretation with.** Model/ANOVA/coefficients, diagnostics, predictions/residuals and five diagnostic charts

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/observed-methods.csv`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Model/ANOVA/coefficients, diagnostics, predictions/residuals and five diagnostic charts
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![OLS regression preparation or calculation context](screenshots/04-author-model.png)

![OLS regression Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 37. Regression bootstrapping

**Use and preparation.** OLS or Logistic setup, enable **Case-resampling bootstrap**, then set samples/workers/seed.

**Practice material.** Corresponding observed-variable fixture

**Begin interpretation with.** Bootstrap coefficient/effect intervals and replicate accounting

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Corresponding observed-variable fixture**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Bootstrap coefficient/effect intervals and replicate accounting
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![Regression bootstrapping preparation or calculation context](screenshots/04-author-model.png)

![Regression bootstrapping Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 38. CB-SEM

**Use and preparation.** **CB-SEM / CFA**, choose the recursive CB-SEM point mode; use raw continuous data and a qualified common-factor model.

**Practice material.** Packaged `samples/recursive-cbsem.csv`

**Begin interpretation with.** Fit indices, parameter estimates, standardized solution, residuals and diagram

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/recursive-cbsem.csv`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Fit indices, parameter estimates, standardized solution, residuals and diagram
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![CB-SEM preparation or calculation context](screenshots/04-author-model.png)

![CB-SEM Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 39. CB-SEM bootstrapping

**Use and preparation.** Same shared row, enable exact case bootstrap and choose supported draws/inference.

**Practice material.** CB-SEM fixture above

**Begin interpretation with.** Point fit plus parameter bootstrap estimates, intervals, probabilities and replicate receipt

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **CB-SEM fixture above**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Point fit plus parameter bootstrap estimates, intervals, probabilities and replicate receipt
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![CB-SEM bootstrapping preparation or calculation context](screenshots/04-author-model.png)

![CB-SEM bootstrapping Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 40. CFA

**Use and preparation.** **CB-SEM / CFA**, choose CFA point mode; reflective common-factor model with no structural regressions.

**Practice material.** Packaged `samples/two-factor-cfa.csv`

**Begin interpretation with.** Fit summary, loadings, variances/covariances, standardized solution and residuals

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **Packaged `samples/two-factor-cfa.csv`**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Fit summary, loadings, variances/covariances, standardized solution and residuals
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![CFA preparation or calculation context](screenshots/04-author-model.png)

![CFA Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

### 41. PCA for CB-SEM preparation

**Use and preparation.** **Principal Component Analysis**; this is exploratory data reduction and does not replace CFA.

**Practice material.** CFA fixture numeric columns

**Begin interpretation with.** Scree, variance, loadings and scores

1. Start QuickPLS. On **Home**, choose **Open Project** for an existing example or **New Project** for a new local `.qpls` file.
2. Open **Data**, choose **Import Data…**, select **CFA fixture numeric columns**, verify the preview and variable types, then choose **Import**.
3. Prepare the model, data roles, group definition, interaction, or saved-model candidates described above. For SEM, verify every construct, indicator assignment, and path direction; for observed-variable methods, verify the selected columns and their roles.
4. Resolve visible model or data blockers and press **Ctrl+S**. A saved writable project will not ask for another Save As when calculation starts.
5. Choose **Calculate…** or press **Ctrl+R**. Use **Find a method** and select the Calculate choice named above. If the row describes an automatic result, select and run the stated parent method instead.
6. Complete the visible required inputs. Keep the supplied defaults for the first practice run. Open **Advanced settings** only for a specialist option, and choose **Method Details** to review purpose, assumptions, limitations, and expected outputs.
7. Read **Readiness**. A red blocker names the exact correction and keeps **Start calculation** disabled. Correct it, reopen Calculate if necessary, and confirm the fixed footer reports that the method is ready.
8. Keep **Open Results when finished** selected and choose **Start calculation** once. Wait for completed result handoff; do not close the project during save, calculation, cancellation, or recovery.
9. In **Results**, confirm the intended run in the upper-left selector. Open the result tree and begin with: Scree, variance, loadings and scores
10. Choose **Save Report** to retain the exact result. Choose **Export…** to select tables and create the required CSV, XLSX, HTML, PDF, SVG, PNG, or canonical JSON output. Close and reopen the project once when practising a complete retained workflow.

![PCA for CB-SEM preparation preparation or calculation context](screenshots/04-author-model.png)

![PCA for CB-SEM preparation Results context](screenshots/05-pls-results.png)

> Practice files demonstrate workflow and output structure. They are not substantive research evidence.

<!-- generated-method-tutorials:end -->

## Packaged practice files

The installer includes a `samples` folder beside the application resources. Use **Data > Import Data** for CSV files and **File > Open Project** for the `.qpls` example.

| File | Best first use |
|---|---|
| `samples/weighted-pls.csv` | Weighted PLS with `case_wt` |
| `samples/group-pls.csv` | MICOM, MGA and group permutation |
| `samples/cta-pls.csv` | Four-indicator CTA-PLS |
| `samples/endogeneity.csv` | Gaussian-copula endogeneity |
| `samples/observed-methods.csv` | PCA, OLS, logistic and NCA |
| `samples/process-path-analysis.csv` | PROCESS/path analysis and bootstrap |
| `samples/two-factor-cfa.csv` | CFA |
| `samples/recursive-cbsem.csv` | Recursive CB-SEM |
| `samples/plspredict.csv` | PLSpredict and CVPAT |
| `samples/higher-order.csv` | Compact higher-order practice |
| `samples/mediation-small.csv` | Minimal mediation practice |
| `samples/ipma.csv` | IPMA practice |
| `samples/model-selection-three-candidate.qpls` | Ready PLS comparison/model-selection project |

These fixtures are intentionally small and deterministic. They demonstrate the workflow and expected output structure; they are not substantive research datasets.

## Explicitly unavailable in QuickPLS 2.62.1

The following five CB-SEM capability cells remain visible or documented as unavailable: covariance/correlation matrix input, CB-SEM model comparison, CB-SEM MGA, scalar/measurement invariance, and CB-SEM moderator analysis. QuickPLS must not fabricate these outputs or route the user to a scientifically different method.

## Release screenshot set and analysis archive

The curated images in `docs/v262/screenshots` come from the qualified 2.62.1 binary. The complete installed-process archive is retained in `docs/v262/process-screenshots/release-binary-2.62.1`; its machine-readable manifest records each image hash, dimensions, viewport, and workflow area. Together they cover:

1. Home and Sample Projects.
2. Data import preview and Import action.
3. Model canvas and Model Issues.
4. Calculate catalog with visible combined-method modes.
5. A selected method with essential inputs, collapsed Advanced settings, Readiness, and the fixed Start calculation footer.
6. Results graphical output with its single contextual toolbar.
7. A wide scientific table with local horizontal scrolling and unchanged columns.
8. Save Report and Export.
9. Regression mode selection and diagnostic results.
10. MultiMod/MGA setup and result.
11. CB-SEM/CFA setup and result.

Tutorial screenshots must come from the exact 2.62.1 release binary. A source mock or an older 2.60/2.61 image is not accepted as 2.62.1 tutorial evidence.

## Scientific status

These tutorials explain operation and interpretation boundaries. They do not claim an independent numerical-oracle comparison for every method; that separate programme was explicitly deferred for this release.