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Related Experiment Video

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Computerized Adaptive Testing System of Functional Assessment of Stroke

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Measurement Efficiency for Fixed-Precision Multidimensional Computerized Adaptive Tests: Comparing Health Measurement

Muirne C S Paap¹, Sebastian Born², Johan Braeken³

¹University of Groningen, The Netherlands.

Applied Psychological Measurement

|December 22, 2018

Summary

Multidimensional computerized adaptive testing (CAT) offers benefits in health assessment, even with different design factors than educational testing. Fixed-precision, multidimensional CAT is effective across various health assessment scenarios.

Keywords:

CAT IRT MIRT PIRLS PROMIS TIMSS computerized adaptive testing item bank item response theory targeting

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Area of Science:

Psychometrics
Health Assessment
Educational Testing

Background:

Computerized adaptive testing (CAT) research is primarily from educational settings.
CAT design factors in health assessment differ significantly from educational testing.
Generalizability of multidimensional CAT (MCAT) to health assessment is unclear.

Purpose of the Study:

To evaluate the impact of key design factors on MCAT performance.
To compare MCAT with separate unidimensional CATs for health and educational scenarios.
To assess the utility of fixed-precision (variable-length) MCAT in health settings.

Main Methods:

Systematic evaluation of MCAT performance using realistic item banks.
Comparison of polytomous items (health) and dichotomous items (education).
Analysis of measurement efficiency for between-item MCAT and unidimensional CATs.

Main Results:

MCAT benefits are observed across diverse health assessment conditions.
Fixed-precision MCAT demonstrates effectiveness comparable to traditional methods.
Design factor impacts vary but do not negate MCAT advantages.

Conclusions:

Fixed-precision multidimensional CAT is a viable and beneficial approach for health assessment.
MCAT principles can be generalized to health assessment despite differing design factors.
Further research should explore MCAT optimization for specific health contexts.