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The Lognormal Race: A Cognitive-Process Model of Choice and Latency with Desirable Psychometric Properties

Published online by Cambridge University Press:  01 January 2025

Jeffrey N. Rouder ,
Jordan M. Province ,
Richard D. Morey ,
Pablo Gomez  and
Andrew Heathcote
Jeffrey N. Rouder*
Affiliation:
University of Missouri
Jordan M. Province
Affiliation:
University of Missouri
Richard D. Morey
Affiliation:
University of Groningen
Pablo Gomez
Affiliation:
Depaul University
Andrew Heathcote
Affiliation:
University of Newcastle
*
Requests for reprints should be sent to Jeffrey N. Rouder, University of Missouri, Columbia, MO, USA. E-mail: [email protected]
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Abstract

We present a cognitive process model of response choice and response time performance data that has excellent psychometric properties and may be used in a wide variety of contexts. In the model there is an accumulator associated with each response option. These accumulators have bounds, and the first accumulator to reach its bound determines the response time and response choice. The times at which accumulator reaches its bound is assumed to be lognormally distributed, hence the model is race or minima process among lognormal variables. A key property of the model is that it is relatively straightforward to place a wide variety of models on the logarithm of these finishing times including linear models, structural equation models, autoregressive models, growth-curve models, etc. Consequently, the model has excellent statistical and psychometric properties and can be used in a wide range of contexts, from laboratory experiments to high-stakes testing, to assess performance. We provide a Bayesian hierarchical analysis of the model, and illustrate its flexibility with an application in testing and one in lexical decision making, a reading skill.

Keywords

cognitive psychometricsresponse-times modelsrace models
Type
Original Paper
Information
Psychometrika , Volume 80 , Issue 2 , June 2015 , pp. 491 - 513
Copyright
Copyright © 2014 The Psychometric Society

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