Module 11: Common Reviewer Problems
Purpose
Many SmartPLS reports are rejected or heavily revised because results are incomplete, overclaimed, or reported without assessment criteria. This module teaches how to avoid those problems.
Learning Objectives
After this module, learners should be able to:
- Identify weak SmartPLS reporting.
- Fix common regression and PLS-SEM reporting errors.
- Respond to reviewer comments with evidence.
- Avoid unsupported causal claims.
Common Problems
| Problem | Better Practice |
|---|---|
| Reporting only p-values | Report coefficient, CI, effect size, and interpretation |
| Ignoring diagnostics | Include model assessment and assumptions |
| Saying "accepted hypothesis" only | Explain direction, size, and support |
| Reporting PLS paths before measurement model | Assess measurement model first |
| No bootstrapping details | Report subsamples, CI method, test type, seed if used |
| No citation for software | Cite SmartPLS properly |
| Causal language from cross-sectional survey | Use association language unless design supports causality |
Reviewer Response Examples
Reviewer:
The authors did not report discriminant validity.
Response:
We added HTMT results to Table X. All HTMT values were below the selected threshold, supporting discriminant validity.
Reviewer:
The regression model does not discuss multicollinearity.
Response:
We added VIF values for all predictors. Values ranged from ... to ..., indicating no severe collinearity.
Reporting Quality Checklist
Before submission:
- Tables match text.
- Hypotheses match paths.
- p-values match significance claims.
- Confidence intervals are interpreted correctly.
- Figures are readable.
- Model limitations are stated.
- SmartPLS citation is included.
Next Module
Continue to Module 12: Capstone SmartPLS Report.