Groups, prediction and segmentation · Tutorial 19 of 41

MICOM

Is the organizational-identification measurement model invariant across the two recorded gender groups?

Supported in 2.62.8

Purpose and applicability

Is the organizational-identification measurement model invariant across the two recorded gender groups?

Prerequisites

  • Use gender as the saved group column and compare its two recorded groups (157 and 148 complete cases)

Do not use it merely because it is available

Use MICOM only when its estimand, data roles and assumptions answer the stated research question. Choose a related estimator or diagnostic when the intended outcome is not among the documented outputs below.

Study preparation

Teaching data
leadership-multigroup.csv
Observations
480
Study type
Deterministic synthetic teaching study
Calculate route
Calculate → MICOM and Multigroup Analysis (PLS / PLSc)

Open the data dictionary and variable-role reference

Model

Organizational Prestige (8 indicators), Organizational Identification (6), Affective Commitment (Joy) (4), and Affective Commitment (Love) (3), all reflective

Organizational Prestige → Organizational Identification; Organizational Identification → Affective Commitment (Joy) and Affective Commitment (Love)

Exact workflow

  1. Download leadership-multigroup.csv and the prepared leadership-multigroup.qpls project. Keep both files in a writable study folder.

  2. Start QuickPLS, choose Open Project, and open the prepared project. Its saved model is already arranged and fitted.

  3. Open Data and confirm that the study contains 480 observations. Return to the model or calculation workspace.

  4. Confirm the saved model specification: Organizational Prestige (8 indicators), Organizational Identification (6), Affective Commitment (Joy) (4), and Affective Commitment (Love) (3), all reflective. Structural specification: Organizational Prestige → Organizational Identification; Organizational Identification → Affective Commitment (Joy) and Affective Commitment (Love).

  5. Confirm that construct labels, indicators, and arrows are readable. The supplied project is saved after Arrange and Fit; do not rearrange it before the tutorial run.

  6. Choose Calculate, then use Calculate → MICOM and Multigroup Analysis (PLS / PLSc).

  7. Review the essential settings listed below. Open Advanced settings only when the design requires a non-default option.

  8. Resolve actionable blockers, review applicability warnings, and leave Open Results when finished selected.

  9. Choose Start calculation. Wait for Completed, then confirm that Results opens for this method.

  10. Inspect the named outputs below in order. Use Save Report, table Copy, or Export as required, then save and reopen the project to confirm the result remains available.

Essential and advanced settings

  • Keep MICOM enabled and review the saved configural checklist
  • Confirm the same measurement specification in both groups
  • Use the saved deterministic seed and 5,000 permutation draws

Keep other advanced controls at their documented defaults unless the study design requires a justified change. Record every non-default value in the research log.

Results to inspect

  1. Pairwise MICOM results
  2. Compositional invariance
  3. Equality of means and variances
  4. Group eligibility and permutation accounting

Interpretation guidance

For MICOM, interpret the listed outputs together with the prerequisite result, the selected settings, model assumptions and data quality. The supplied values are instructional; they are not validation against an external paper or another software package.

Reporting guidance

Report the QuickPLS version, MICOM route, sample size, model or variable roles, preprocessing, essential settings, non-default advanced settings, and the named primary outputs. Retain the project, data checksum and exported table used in the manuscript.

Common mistakes and recovery

  • Running the method before completing its prerequisite calculation.
  • Changing the data, model or variable roles after the prerequisite result was saved.
  • Treating an unavailable or not-applicable value as zero.
  • Reporting an estimate without its method-appropriate uncertainty or diagnostic context.

Open calculation and Results troubleshooting

Screen-by-screen evidence

Images shown here are mapped to this tutorial’s required installed-application evidence. Missing captures are labelled explicitly and are not replaced with generic screenshots.

Step 1: Imported teaching dataset is open
Step 3: The prepared project opens with its saved, neatly arranged model diagram
Step 6: Correct method and required settings are visible
Step 9: Primary MICOM result is visible
Step 9: Second important MICOM result is visible

Limitations and related methods

This tutorial verifies the documented workflow and outputs for its supplied teaching fixture. It does not establish numerical identity with another package, replace method literature, or guarantee that the method is suitable for a different study.

Related methods in this family