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A Joint Cognitive Latent Variable Model for Binary Decision-making Tasks and Reaction Time Outcomes

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  • Mahdi Mollakazemiha

    (Shahid Beheshti University)

  • Ehsan Bahrami Samani

    (Shahid Beheshti University)

Abstract

Traditionally, in cognitive modeling for binary decision-making tasks, stochastic differential equations, particularly a family of diffusion decision models, are applied. These models suffer from difficulties in parameter estimation and forecasting due to the non-existence of analytical solutions for the differential equations. In this paper, we introduce a joint latent variable model for binary decision-making tasks and reaction time outcomes. Additionally, accelerated Failure Time models can be used for the analysis of reaction time to estimate the effects of covariates on acceleration/deceleration of the survival time. A full likelihood-based approach is used to obtain maximum likelihood estimates of the parameters of the model.To illustrate the utility of the proposed models, a simulation study and real data are analyzed.

Suggested Citation

  • Mahdi Mollakazemiha & Ehsan Bahrami Samani, 2025. "A Joint Cognitive Latent Variable Model for Binary Decision-making Tasks and Reaction Time Outcomes," Annals of Data Science, Springer, vol. 12(2), pages 499-516, April.
    • Handle: RePEc:spr:aodasc:v:12:y:2025:i:2:d:10.1007_s40745-024-00519-2
    DOI: 10.1007/s40745-024-00519-2
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    References listed on IDEAS

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    1. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
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