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Related Experiment Video

Updated: Jul 10, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Joint partial credit and time model.

Inhan Kang¹

¹Department of Psychology, College of Liberal Arts, Yonsei University, 403 Widang Hall, 50 Yonsei-ro, Seoul, Seodaemun-gu, 03722, Republic of Korea. qpsy@yonsei.ac.kr.

Behavior Research Methods

|July 8, 2026

Summary

This summary is machine-generated.

This study introduces the Joint Partial Credit and Time Model (JPCTM) for analyzing partial credit scores and response times (RTs). The JPCTM improves measurement accuracy by accounting for RT variations across score categories, leading to more stable ability estimates.

Keywords:

Hierarchical framework Item response theory Partial credit Psychological and educational measurement Response times

Related Experiment Videos

Last Updated: Jul 10, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Area of Science:

Psychometric modeling
Educational measurement
Cognitive psychology

Background:

Joint modeling of responses and response times (RTs) is increasingly used in psychological and educational measurement.
Limited understanding exists regarding RT patterns within partial credit settings.
Heterogeneity in RTs across score categories can impact measurement accuracy.

Purpose of the Study:

Introduce the Joint Partial Credit and Time Model (JPCTM) for analyzing partial credit scores and RTs.
Investigate the utility of incorporating varying intercepts (VI) and cross-loadings (CL) to capture RT heterogeneity.
Enhance the precision of individual performance estimates in partial credit contexts.

Main Methods:

Developed the Joint Partial Credit and Time Model (JPCTM) using a hierarchical framework, the generalized partial credit model for scores, and a log-normal distribution for RTs.
Extended the JPCTM with varying intercepts (VI) and/or cross-loadings (CL) to account for RT heterogeneity across score categories.
Conducted simulation studies and empirical applications to evaluate model performance and parameter recovery.

Main Results:

The JPCTM with VI and CL demonstrated good parameter recovery under various conditions in simulations.
Empirical analyses confirmed systematic differences in RTs across tests, items, and score categories.
Jointly modeling partial credit scores and RTs reduced the standard errors of ability estimates.

Conclusions:

The JPCTM offers a comprehensive approach to modeling partial credit data with associated RTs.
The model effectively captures RT heterogeneity across score categories, improving measurement precision.
Joint modeling of scores and RTs yields more stable and accurate measures of individual performance compared to response-only models.