Method reference · QuickPLS 2.62.8
Method tutorials
Choose a supported procedure for its research question, preparation, exact Calculate route, settings, outputs, realistic teaching data, and evidence screens.
Offline tutorial downloads
| Method | Family | Route and study question | Status |
|---|---|---|---|
| PLS-SEM Algorithm 400 observations in the supplied study | Estimation and core analysis | Calculate → PLS-SEM Algorithm How do perceived quality, value, and trust shape satisfaction and customer loyalty? | Supported |
| PLS power analysis 400 observations in the supplied study | Estimation and core analysis | Calculate → PLS-SEM Sample Size and Power What power is expected for a Quality → Loyalty path of 0.30 at planned sample sizes of 80 and 120? | Supported |
| Weighted PLS 360 observations in the supplied study | Estimation and core analysis | Calculate → Weighted PLS Do service, fairness, and satisfaction predict retention after applying case weights? | Supported |
| Consistent PLS 400 observations in the supplied study | Estimation and core analysis | Calculate → Consistent PLS How do the customer-experience relationships look after consistent-PLS correction of reflective constructs? | Supported |
| Principal Component Analysis 360 observations in the supplied study | Estimation and core analysis | Calculate → Principal Component Analysis How many empirical components summarize the twelve academic-engagement items? | Supported |
| PLS-SEM Bootstrapping 420 observations in the supplied study | Resampling and inference | Calculate → PLS-SEM Bootstrapping Which structural and measurement-model estimates have stable bootstrap inference? | Supported |
| PLSc Consistent Bootstrapping 400 observations in the supplied study | Resampling and inference | Calculate → PLSc Consistent Bootstrapping Are the consistently corrected reflective-model estimates stable under resampling? | Supported |
| Blindfolding 400 observations in the supplied study | Resampling and inference | Calculate → PLS-SEM Algorithm → Results → Blindfolding — cross-validated redundancy Does the model show predictive relevance for Trust, Satisfaction, and Loyalty? | Supported |
| Permutation / Structural Path Randomization 305 observations in the supplied study | Resampling and inference | Calculate → Structural Path Randomization Is the Leadership → Commitment path stronger than expected under structural-path randomization? | Supported |
| PLSc Consistent Permutation 480 observations in the supplied study | Resampling and inference | Calculate → PLSc Consistent Permutation Do consistently corrected path estimates differ between on-site and hybrid employees? | Supported |
| CVPAT 420 observations in the supplied study | Quality and validation | Calculate → PLSpredict / CVPAT Does the loyalty model predict better than its comparison benchmark across held-out folds? | Supported |
| Confirmatory Composite Analysis 400 observations in the supplied study | Quality and validation | Calculate → CCA composite residual diagnostics How closely does the composite model reproduce the observed indicator correlations? | Supported |
| Confirmatory Tetrad Analysis 320 observations in the supplied study | Quality and validation | Calculate → Confirmatory Tetrad Analysis Does the four-item Innovation Capability block show the tetrad pattern expected for its measurement specification? | Supported |
| HTMT / HTMT+ 400 observations in the supplied study | Quality and validation | Calculate → PLS-SEM Algorithm → Results → HTMT+ and HTMT — original signed correlations Are the five customer-experience constructs empirically distinct? | Supported |
| Global GoF 400 observations in the supplied study | Fit and model selection | Calculate → Global Goodness of Fit What is the legacy descriptive global GoF summary for this reflective PLS model? | Supported |
| PLS Model Fit 400 observations in the supplied study | Fit and model selection | Calculate → PLS-SEM Algorithm; Model Fit is produced automatically What descriptive model-fit diagnostics accompany the customer-experience PLS estimate? | Supported |
| PLS Model Comparison 305 observations in the supplied study | Fit and model selection | Calculate → PLS Model Comparison Does adding a direct Organizational Prestige → Affective Commitment (Joy) path improve prediction over the established mediated model? | Supported |
| Prediction-Oriented Model Selection 305 observations in the supplied study | Fit and model selection | Calculate → Prediction-Oriented Model Selection Which of three organizational-identification models should be retained when equation-level predictive evidence is the primary criterion? | Supported |
| MICOM 480 observations in the supplied study | Groups, prediction and segmentation | Calculate → MICOM and Multigroup Analysis (PLS / PLSc) Is the organizational-identification measurement model invariant across the two recorded gender groups? | Supported |
| PLS-MGA 305 observations in the supplied study | Groups, prediction and segmentation | Calculate → MICOM and Multigroup Analysis (PLS / PLSc) Does the Organizational Identification → Affective Commitment (Joy) relationship differ between the two recorded gender groups? | Supported |
| PLSc-MGA 480 observations in the supplied study | Groups, prediction and segmentation | Calculate → MICOM and Multigroup Analysis (PLS / PLSc) Do consistently corrected leadership effects differ between the two work modes? | Supported |
| PLSpredict 420 observations in the supplied study | Groups, prediction and segmentation | Calculate → PLSpredict / CVPAT How accurately does the model predict Loyalty indicators in held-out data? | Supported |
| PLS-POS 305 observations in the supplied study | Groups, prediction and segmentation | Calculate → PLS-POS in the shared MultiMod workspace Can prediction-oriented segmentation identify a stable two-segment structure in the organizational-identification model? | Supported |
| FIMIX-PLS 600 observations in the supplied study | Groups, prediction and segmentation | Calculate → FIMIX-PLS in the shared MultiMod workspace Does finite-mixture PLS reveal latent customer classes with distinct renewal behavior? | Supported |
| IPMA 400 observations in the supplied study | Advanced PLS analysis | Calculate → Importance-Performance Map Analysis Which antecedents of Loyalty combine high importance with comparatively low performance? | Supported |
| Moderation 305 observations in the supplied study | Advanced PLS analysis | Calculate → PLS-SEM Algorithm Does Organizational Prestige change how Organizational Identification relates to Affective Commitment (Joy) and Affective Commitment (Love)? | Supported |
| Mediation 420 observations in the supplied study | Advanced PLS analysis | Calculate → PLS-SEM Bootstrapping How much of training quality's association with job performance operates through self-efficacy and training transfer? | Supported |
| Nonlinear relationships 344 observations in the supplied study | Advanced PLS analysis | Calculate → Quadratic Nonlinear Effects Does attractiveness have a curved relationship with competence after accounting for the wider corporate-reputation model? | Supported |
| Higher-order models 305 observations in the supplied study | Advanced PLS analysis | Calculate → PLS-SEM Algorithm after authoring the higher-order construct Can the joy and love dimensions form a reflective-reflective Affective Commitment construct, and how do organizational prestige and identification predict it? | Supported |
| Gaussian-copula endogeneity 420 observations in the supplied study | Advanced PLS analysis | Calculate → Gaussian-Copula Endogeneity Diagnostics Is the Trust → Renewal effect sensitive to potential endogeneity detected with a Gaussian copula? | Supported |
| GSCA 360 observations in the supplied study | General statistical methods | Calculate → GSCA How do supply-chain capabilities combine into resilience and performance in a component model? | Supported |
| Binary logistic regression 500 observations in the supplied study | General statistical methods | Calculate → Regression → Binary logistic Which business characteristics predict customer churn? | Supported |
| Necessary Condition Analysis 360 observations in the supplied study | General statistical methods | Calculate → Necessary Condition Analysis Is digital capability necessary, though not necessarily sufficient, for high innovation performance? | Supported |
| PROCESS/path analysis 500 observations in the supplied study | General statistical methods | Calculate → Regression → Graph-defined Path Analysis / PROCESS Does analytics capability influence business performance through organizational agility, conditional on market turbulence? | Supported |
| PROCESS bootstrapping 500 observations in the supplied study | General statistical methods | Calculate → Regression → Graph-defined Path Analysis / PROCESS, then enable Case-resampling bootstrap Are the indirect and conditional effects in the agility mediation model stable under case resampling? | Supported |
| OLS regression 500 observations in the supplied study | General statistical methods | Calculate → Regression → Ordinary least squares How do digital investment, analytics capability, agility, and market turbulence explain business performance? | Supported |
| Regression bootstrapping 500 observations in the supplied study | General statistical methods | Calculate → Regression, choose OLS or Binary logistic, then enable Case-resampling bootstrap How stable are the OLS and logistic coefficient estimates under case resampling? | Supported |
| CB-SEM 500 observations in the supplied study | CB-SEM and CFA | Calculate → CB-SEM / CFA → Recursive CB-SEM point mode Does the recursive common-factor service-recovery model reproduce the covariance structure adequately? | Supported |
| CB-SEM bootstrapping 500 observations in the supplied study | CB-SEM and CFA | Calculate → CB-SEM / CFA, enable exact case bootstrap How stable are the recursive CB-SEM parameters under exact case bootstrapping? | Supported |
| CFA 500 observations in the supplied study | CB-SEM and CFA | Calculate → CB-SEM / CFA → CFA point mode Does the proposed four-factor student-wellbeing measurement model fit the observed covariance structure? | Supported |
| PCA for CB-SEM preparation 500 observations in the supplied study | CB-SEM and CFA | Calculate → Principal Component Analysis What exploratory component pattern appears before fitting the confirmatory wellbeing model? | Supported |
| CB-SEM Model Comparison | CB-SEM and CFA | No qualified Standard execution route is available in 2.62.8. | Unavailable |
| CB-SEM Multigroup Analysis | CB-SEM and CFA | No qualified Standard execution route is available in 2.62.8. | Unavailable |
| CB-SEM Measurement Invariance | CB-SEM and CFA | No qualified Standard execution route is available in 2.62.8. | Unavailable |
| CB-SEM Moderator Analysis | CB-SEM and CFA | No qualified Standard execution route is available in 2.62.8. | Unavailable |
| CB-SEM-specific PCA capability cell | CB-SEM and CFA | Use the ordinary Principal Component Analysis route for exploratory preparation; the separate CB-SEM capability cell remains unavailable. | Unavailable |