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Video 2 Chapter 5 Formative measurement

Formative Measurement Model Assessment

Assessing formatively measured constructs: redundancy analysis for convergent validity, indicator collinearity via VIF, and interpreting outer weights and their significance.

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What you'll learn

  • Distinguish formative from reflective measurement — conceptually and in SEMinR syntax
  • Run a redundancy analysis to establish convergent validity
  • Check indicator collinearity with VIF and diagnose problematic indicators
  • Interpret outer weights, their bootstrap significance, and outer loadings as a secondary check

R practice in this video

  • > Comment the *why*, not the *what*

Coming soon

This tutorial pairs with Video 2 in the series. Full write-up will land when the video is published. In the meantime, Chapter 5 of Hair et al. (2026) has the complete theoretical treatment, and the code file seminr-primer-v2-chap5.R in the companion repo has the runnable example.

What this tutorial will cover

  • Why the composite() / reflective() choice in SEMinR is separate from the formative/reflective assessment decision
  • Redundancy analysis — the cleanest test for convergent validity in formatively measured constructs
  • VIF thresholds and what to do when collinearity is too high
  • Reading outer weights vs outer loadings and which one matters for which argument
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