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Monte Carlo Evaluation of Two-Level Logistic Regression for Assessing Person Fit.
1a Washington University in St. Louis .
Multivariate Behavioral Research
|January 21, 2016
Summary
This study evaluated Reise
Area of Science:
- Psychometrics
- Educational Measurement
- Psychological Assessment
Background:
- Person fit assesses how well individual examinees align with item response models.
- Reise's (2000) two-level logistic regression method for person fit analysis remained unevaluated.
- Aberrant response patterns can bias psychometric analyses.
Purpose of the Study:
- To apply and evaluate Reise's (2000) two-level logistic regression for person fit analysis.
- To assess the method's performance with empirical data and under simulation conditions.
- To compare its efficacy against the established lz person-fit statistic.
Main Methods:
- Application of Reise's (2000) two-level logistic regression to empirical data.
- Simulation study manipulating aberrancy type, test reliability, and scale length.
- Comparison of detection rates with the lz person-fit statistic.
Main Results:
- Reise's method successfully identified aberrant individuals in empirical data.
- Detection power varied with aberrancy type, reliability, and scale length.
- The method performed comparably to or better than the lz statistic.
Conclusions:
- Reise's (2000) method is a viable tool for detecting person fit heterogeneity.
- The approach offers a valuable alternative for identifying aberrant responders.
- Further research should explore its application in diverse psychometric contexts.
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