Accounting for individual differences in speed in the discretized signed residual time model. (22nd December 2020)

• Record Type: Journal Article
• Authors: Tijmstra, Jesper; Bolsinova, Maria
• Is Part Of: British journal of mathematical & statistical psychology. Volume 74(2021)Supplement 1
• Page Start: 176
• Page End: 198
• Publication Date: 2020-12-22
• Subjects: Signed residual time model -- Response time -- Response speed -- Item response theory -- Ability measurement; Psychometrics -- Periodicals; Psychology -- Mathematical models -- Periodicals; Psychology -- Statistical methods -- Periodicals; 150.727
• DOI: 10.1111/bmsp.12223
• Languages: English
• ISSNs: 0007-1102

Abstract

Abstract : With advances in computerized tests, it has become commonplace to register not just the accuracy of the responses provided to the items, but also the response time. The idea that for each response both response accuracy and response time are indicative of ability has explicitly been incorporated in the signed residual time (SRT) model (Maris & van der Maas, 2012, Psychometrika, 77, 615–633), which assumes that fast correct responses are indicative of a higher level of ability than slow correct responses. While the SRT model allows one to gain more information about ability than is possible based on considering only response accuracy, measurement may be confounded if persons show differences in their response speed that cannot be explained by ability, for example due to differences in response caution. In this paper we propose an adapted version of the SRT model that makes it possible to model person differences in overall speed, while maintaining the idea of the SRT model that the speed at which individual responses are given may be indicative of ability. We propose a two‐dimensional SRT model that considers dichotomized response time, which allows one to model differences between fast and slow responses. The model includes both an ability and a speed parameter, and allows one to correct the estimates of ability for possible differences in overall speed. The performance of the model is evaluated through simulation, and the relevance of including the speed parameter is studied in the context of an empirical example from formative educational assessment.