Fit and model selection · Tutorial 17 of 41

PLS Model Comparison

Does adding a direct Organizational Prestige → Affective Commitment (Joy) path improve prediction over the established mediated model?

Supported in 2.62.8

Purpose and applicability

Does adding a direct Organizational Prestige → Affective Commitment (Joy) path improve prediction over the established mediated model?

Prerequisites

  • Use the prepared project because it retains both qualified comparison candidates and their ordinary PLS results

Do not use it merely because it is available

Use PLS Model Comparison 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
organizational-identification-model-comparison.csv
Observations
305
Study type
Deterministic synthetic teaching study
Calculate route
Calculate → PLS Model Comparison

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

Reference model: Prestige → Identification; Identification → Joy and Love. Calculated alternative: retain those paths and add Prestige → Joy

Exact workflow

  1. Download organizational-identification-model-comparison.csv and the prepared organizational-identification-model-comparison.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 305 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: Reference model: Prestige → Identification; Identification → Joy and Love. Calculated alternative: retain those paths and add Prestige → Joy.

  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 → PLS Model Comparison.

  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

  • Select Organizational Identification Model as Reference and the calculated alternative revision as Alternative
  • Use the shared 10-fold, 10-repeat paired comparison plan, 95% confidence, and the saved deterministic seed

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. Comparison overview
  2. Predictive loss
  3. Paired CVPAT
  4. BIC
  5. Decision evidence

Interpretation guidance

For PLS Model Comparison, 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, PLS Model Comparison 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 PLS Model Comparison result is visible
Step 9: Second important PLS Model Comparison 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