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Psychometric Modeling of Response Speed and Accuracy with Mixed and Conditional Regression

Published online by Cambridge University Press:  01 January 2025

Gerard J. P. Van Breukelen
Gerard J. P. Van Breukelen*
Affiliation:
Maastricht University, The Netherlands
*
Requests for reprints should be sent to Gerard J.P. Van Breukelen, Department of Methodology and Statistics, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands. E-mail: gerard.vbreukelen@stat.unimaas.nl
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Abstract

Human performance in cognitive testing and experimental psychology is expressed in terms of response speed and accuracy. Data analysis is often limited to either speed or accuracy, and/or to crude summary measures like mean response time (RT) or the percentage correct responses. This paper proposes the use of mixed regression for the psychometric modeling of response speed and accuracy in testing and experiments. Mixed logistic regression of response accuracy extends logistic item response theory modeling to multidimensional models with covariates and interactions. Mixed linear regression of response time extends mixed ANOVA to unbalanced designs with covariates and heterogeneity of variance. Related to mixed regression is conditional regression, which requires no normality assumption, but is limited to unidimensional models. Mixed and conditional methods are both applied to an experimental study of mental rotation. Univariate and bivariate analyzes show how within-subject correlation between response and RT can be distinguished from between-subject correlation, and how latent traits can be detected, given careful item design or content analysis. It is concluded that both response and RT must be recorded in cognitive testing, and that mixed regression is a versatile method for analyzing test data.

Keywords

time limit testsconditional accuracy functionspeed-accuracy tradeoffconditional logistic regressionCox regressionmixed regressionmultilevel analysislatent traitmental rotation

Information

Type
Original Paper
Information
Psychometrika , Volume 70 , Issue 2 , June 2005 , pp. 359 - 376
Copyright
Copyright © 2005 The Psychometric Society

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Footnotes

I am grateful to Rogier Donders for putting his data at my disposal.

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