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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
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Multilevel multidimensional item response model with a multilevel latent covariate.

Sun-Joo Cho1, Brian Bottge2

  • 1Vanderbilt University, Nashville, Tennessee, USA.

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This study introduces a new statistical model to accurately measure intervention effects in educational tests. It corrects for measurement errors in pre-test and post-test scores for more reliable results.

Keywords:
measurement errormultidimensional item response modelmultilevel model

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Area of Science:

  • Educational Measurement
  • Psychometrics
  • Statistical Modeling

Background:

  • Intervention effect estimation commonly uses pre-test and post-test scores.
  • Ignoring measurement error in test scores can bias intervention effect estimates.
  • Analyzing individual domains within test data can provide more nuanced insights.

Purpose of the Study:

  • To present a statistical model that adjusts for measurement error in both response and covariate variables.
  • To estimate intervention effects more accurately within specific domains of test data.
  • To apply the multilevel multidimensional item response model for improved intervention analysis.

Main Methods:

  • Utilized a pre-test-post-test cluster randomized trial design.
  • Applied a multilevel multidimensional item response model.
  • Incorporated measurement error adjustments for response and covariate variables.

Main Results:

  • The proposed model provides adjusted estimates of intervention effects for each domain.
  • Accounting for measurement error leads to less biased intervention effect detection.
  • Domain-specific analysis offers a more informative evaluation of intervention impact.

Conclusions:

  • The multilevel multidimensional item response model with measurement error adjustments is a valuable tool for educational research.
  • Accurate estimation of intervention effects requires addressing measurement error in test scores.
  • Domain-specific analysis enhances the understanding of intervention effectiveness.