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Semi-parametric proportional hazards models with crossed random effects for psychometric response times.
Br J Math Stat Psychol. 2014 May; 67(2):304-27.BJ

Abstract

The semi-parametric proportional hazards model with crossed random effects has two important characteristics: it avoids explicit specification of the response time distribution by using semi-parametric models, and it captures heterogeneity that is due to subjects and items. The proposed model has a proportionality parameter for the speed of each test taker, for the time intensity of each item, and for subject or item characteristics of interest. It is shown how all these parameters can be estimated by Markov chain Monte Carlo methods (Gibbs sampling). The performance of the estimation procedure is assessed with simulations and the model is further illustrated with the analysis of response times from a visual recognition task.

Authors+Show Affiliations

Ghent University, Belgium.No affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

23937392

Citation

Loeys, Tom, et al. "Semi-parametric Proportional Hazards Models With Crossed Random Effects for Psychometric Response Times." The British Journal of Mathematical and Statistical Psychology, vol. 67, no. 2, 2014, pp. 304-27.
Loeys T, Legrand C, Schettino A, et al. Semi-parametric proportional hazards models with crossed random effects for psychometric response times. Br J Math Stat Psychol. 2014;67(2):304-27.
Loeys, T., Legrand, C., Schettino, A., & Pourtois, G. (2014). Semi-parametric proportional hazards models with crossed random effects for psychometric response times. The British Journal of Mathematical and Statistical Psychology, 67(2), 304-27. https://doi.org/10.1111/bmsp.12020
Loeys T, et al. Semi-parametric Proportional Hazards Models With Crossed Random Effects for Psychometric Response Times. Br J Math Stat Psychol. 2014;67(2):304-27. PubMed PMID: 23937392.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Semi-parametric proportional hazards models with crossed random effects for psychometric response times. AU - Loeys,Tom, AU - Legrand,Catherine, AU - Schettino,Antonio, AU - Pourtois,Gilles, Y1 - 2013/08/13/ PY - 2012/04/28/received PY - 2013/06/10/revised PY - 2013/8/14/entrez PY - 2013/8/14/pubmed PY - 2015/7/7/medline KW - Bayesian estimation KW - crossed random effects KW - frailty model KW - response time KW - semi-parametric proportional hazards model SP - 304 EP - 27 JF - The British journal of mathematical and statistical psychology JO - Br J Math Stat Psychol VL - 67 IS - 2 N2 - The semi-parametric proportional hazards model with crossed random effects has two important characteristics: it avoids explicit specification of the response time distribution by using semi-parametric models, and it captures heterogeneity that is due to subjects and items. The proposed model has a proportionality parameter for the speed of each test taker, for the time intensity of each item, and for subject or item characteristics of interest. It is shown how all these parameters can be estimated by Markov chain Monte Carlo methods (Gibbs sampling). The performance of the estimation procedure is assessed with simulations and the model is further illustrated with the analysis of response times from a visual recognition task. SN - 2044-8317 UR - https://www.unboundmedicine.com/medline/citation/23937392/Semi_parametric_proportional_hazards_models_with_crossed_random_effects_for_psychometric_response_times_ L2 - https://doi.org/10.1111/bmsp.12020 DB - PRIME DP - Unbound Medicine ER -