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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
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Measuring change for a multidimensional test using a generalized explanatory longitudinal item response model.

Sun-Joo Cho1, Michele Athay, Kristopher J Preacher

  • 1Peabody College of Vanderbilt University, Nashville, TN 37203-5721, USA. sj.cho@vanderbilt.edu

The British Journal of Mathematical and Statistical Psychology
|October 23, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a new longitudinal item response theory model to measure individual differences in change for multidimensional tests. The model helps explain changes in scores across different groups and item types.

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Area of Science:

  • Psychometrics
  • Educational Measurement
  • Longitudinal Data Analysis

Background:

  • Multidimensional tests are common in education and psychology.
  • Measuring individual differences in change within Item Response Theory (IRT) is under-researched.

Purpose of the Study:

  • To propose a generalized explanatory longitudinal item response model for measuring individual differences in change.
  • To extend existing unidimensional models and introduce new multidimensional models within an IRT framework.

Main Methods:

  • Development of a generalized explanatory longitudinal item response model.
  • Implementation using software for generalized linear models.
  • Application to multidimensional tests with person and item groups.

Main Results:

  • The proposed models effectively measure individual differences in change.
  • Longitudinal models can explain score changes for different person groups (e.g., learning disabled students).
  • Models can account for variations in item difficulties across item domains.

Conclusions:

  • The generalized explanatory longitudinal IRT model offers a robust framework for analyzing change in multidimensional assessments.
  • This approach enhances understanding of individual differences in growth and performance across various skills and groups.