Literature DB >> 26742003

Response Time Modeling Based on the Proportional Hazards Model.

Jochen Ranger1, Tuulia M Ortner2.   

Abstract

Response time data are regularly analyzed in psychology. When several response times are assessed per participant, it is common practice to use latent trait models in order to account for the dependency of the response times from the same participant. One such model is the proportional hazards model with random effects. Despite its popularity in survival analysis, this model is rarely used in psychology because of the difficulty of model estimation when latent variables are present. In this article, a new estimation method is proposed. This method is based on the rank correlation matrix containing Kendall's Tau coefficients and unweighted least squares estimation ( Kendall, 1938 ). Compared with marginal maximum likelihood estimation, the new estimation approach is simple, not computationally intensive, and almost as efficient. Additionally, the approach allows the implementation of a test for model fit. Feasibility of the estimation method and validity of the fit test is demonstrated with a simulation study. An application of the model to a real data set is provided.

Entities:  

Year:  2013        PMID: 26742003     DOI: 10.1080/00273171.2013.796280

Source DB:  PubMed          Journal:  Multivariate Behav Res        ISSN: 0027-3171            Impact factor:   5.923


  3 in total

1.  A Mixture Proportional Hazards Model With Random Effects for Response Times in Tests.

Authors:  Jochen Ranger; Jörg-Tobias Kuhn
Journal:  Educ Psychol Meas       Date:  2015-08-13       Impact factor: 2.821

2.  Semiparametric Factor Analysis for Item-Level Response Time Data.

Authors:  Yang Liu; Weimeng Wang
Journal:  Psychometrika       Date:  2022-01-31       Impact factor: 2.500

3.  A heteroscedastic generalized linear model with a non-normal speed factor for responses and response times.

Authors:  Dylan Molenaar; Maria Bolsinova
Journal:  Br J Math Stat Psychol       Date:  2017-02-03       Impact factor: 3.380

  3 in total

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