Literature DB >> 22011034

A latent trait model for response times on tests employing the proportional hazards model.

Jochen Ranger1, Tuulia Ortner.   

Abstract

For computer-administered tests, response times can be recorded conjointly with the corresponding responses. This broadens the scope of potential modelling approaches because response times can be analysed in addition to analysing the responses themselves. For this purpose, we present a new latent trait model for response times on tests. This model is based on the Cox proportional hazards model. According to this model, latent variables alter a baseline hazard function. Two different approaches to item parameter estimation are described: the first approach uses a variant of the Cox model for discrete time, whereas the second approach is based on a profile likelihood function. Properties of each estimator will be compared in a simulation study. Compared to the estimator for discrete time, the profile likelihood estimator is more efficient, that is, has smaller variance. Additionally, we show how the fit of the model can be evaluated and how the latent traits can be estimated. Finally, the applicability of the model to an empirical data set is demonstrated. ©2011 The British Psychological Society.

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Year:  2011        PMID: 22011034     DOI: 10.1111/j.2044-8317.2011.02032.x

Source DB:  PubMed          Journal:  Br J Math Stat Psychol        ISSN: 0007-1102            Impact factor:   3.380


  6 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.  Application of Change Point Analysis of Response Time Data to Detect Test Speededness.

Authors:  Ying Cheng; Can Shao
Journal:  Educ Psychol Meas       Date:  2021-09-20       Impact factor: 3.088

4.  On the Speed Sensitivity Parameter in the Lognormal Model for Response Times and Implications for High-Stakes Measurement Practice.

Authors:  Benjamin Becker; Dries Debeer; Sebastian Weirich; Frank Goldhammer
Journal:  Appl Psychol Meas       Date:  2021-06-09

5.  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

6.  Joint Modeling of Response Accuracy and Time in Between-Item Multidimensional Tests Based on Bi-Factor Model.

Authors:  Xiaojun Guo; Yuyue Jiao; ZhengZheng Huang; TieChuan Liu
Journal:  Front Psychol       Date:  2022-04-11
  6 in total

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