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Studying Factorial Invariance With Nominal Items: A Note on a Latent Variable Modeling Procedure.

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  • 1Michigan State University, East Lansing, USA.

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Summary

This study introduces a new latent variable modeling method to assess measurement invariance and item bias in multi-component instruments with nominal items. The procedure helps identify specific item issues without needing a reference variable.

Keywords:
differential item functioningfactorial invariancefalse discovery ratelatent variable modelinglikelihood ratio testmultiple testingnominal item

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Area of Science:

  • Psychometrics
  • Statistical Modeling
  • Measurement Theory

Background:

  • Assessing factorial invariance and differential item functioning (DIF) is crucial for multi-component instruments.
  • Existing methods may require reference variables or struggle with nominal item data.
  • Identifying localized invariance violations is essential for valid measurement.

Purpose of the Study:

  • To present a novel latent variable modeling procedure for factorial invariance and DIF analysis.
  • To accommodate multi-component instruments with nominal items.
  • To enable the localization of individual invariance violations without a reference variable.

Main Methods:

  • A latent variable modeling approach is employed.
  • The method utilizes a multiple testing framework incorporating the false discovery rate (FDR) concept.
  • Likelihood ratio tests are applied to detect invariance violations.

Main Results:

  • The procedure effectively analyzes factorial invariance and DIF for nominal items.
  • It complements existing approaches by offering localized violation detection.
  • The method successfully identifies specific item-level invariance issues.

Conclusions:

  • The proposed latent variable modeling procedure offers a robust approach to measurement invariance and DIF analysis.
  • It is particularly useful for instruments with nominal items and complex structures.
  • The ability to localize individual invariance violations enhances the interpretability and validity of measurement instruments.