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Using latent class analysis to justify a latent continuum in item development.

Jay Verkuilen1, Sydne T McCluskey1, Magdalen Beiting-Parrish2

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Latent Class Analysis (LCA) helps validate if assessment items measure a continuous trait, supporting Classical Test Theory and Item Response Theory. LCA offers a flexible, understandable method for item development and adaptation.

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Area of Science:

  • Psychometrics
  • Educational Measurement
  • Statistical Modeling

Background:

  • Classical Test Theory (CTT) and Item Response Theory (IRT) rely on the assumption of a latent continuum.
  • Item development and adaptation require methods to justify this critical assumption.
  • Existing methods may have limitations with complex data structures or non-technical interpretation.

Purpose of the Study:

  • To demonstrate the utility of exploratory Latent Class Analysis (LCA) in item development and adaptation.
  • To show how LCA can be used to justify the latent continuum assumption essential for CTT and IRT.
  • To highlight LCA's advantages in handling design issues and its interpretability for diverse stakeholders.

Main Methods:

  • Exploratory Latent Class Analysis (LCA) was employed.
  • LCA statistics, specifically contrasts of predicted probabilities (informed by Kelley's discrimination index logic), were analyzed.
  • Simulated data mimicking pilot mathematics assessments were used for illustration.

Main Results:

  • LCA statistics effectively indicate whether items align with the latent continuum assumption.
  • LCA demonstrates flexibility in managing planned missingness and mixed item types, unlike CTT.
  • LCA provides more accessible output for non-technical users compared to IRT.

Conclusions:

  • Exploratory LCA is a valuable tool for justifying the latent continuum assumption in item development.
  • LCA offers a robust and interpretable alternative for psychometric analyses, particularly for complex datasets.
  • The method supports rigorous assessment development and adaptation across various fields.