ERIC Number: EJ720507
Record Type: Journal
Publication Date: 2005-Jun
Reference Count: 46
Psychometric Modeling of Response Speed and Accuracy with Mixed and Conditional Regression
Van Breukelen, Gerard J. P.
Psychometrika, v70 n2 p359-376 Jun 2005
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 analyses 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.
Descriptors: Regression (Statistics), Psychometrics, Testing, Reaction Time, Psychological Studies, Item Response Theory, Response Style (Tests), Cognitive Tests
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Authoring Institution: N/A