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A Latent Variable Model for Discrete Multivariate Psychometric Waiting Times

Published online by Cambridge University Press:  01 January 2025

Jeffrey A. Douglas ,
Michael R. Kosorok  and
Betty A. Chewning
Jeffrey A. Douglas*
Affiliation:
Department of Biostatistics, University of Wisconsin-Madison
Michael R. Kosorok
Affiliation:
Departments of Statistics and Biostatistics, University of Wisconsin-Madison
Betty A. Chewning
Affiliation:
School of Pharmacy, University of Wisconsin-Madison
*
Requests for reprints should be sent to Jeffrey A. Douglas, Department of Biostatistics, K6-446 Clinical Science Center, University of Wisconsin, 600 Highland Avenue, Madison, WI 53792. E-mail: [email protected]
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Abstract

A version of the discrete proportional hazards model is developed for psychometrical applications. In such applications, a primary covariate that influences failure times is a latent variable representing a psychological construct. The Metropolis-Hastings algorithm is studied as a method for performing marginal likelihood inference on the item parameters. The model is illustrated with a real data example that relates the age at which teenagers first experience various substances to the latent ability to avoid the onset of such behaviors.

Keywords

latent variablefrailtyMetropolis-Hastings algorithmsurvival analysis
Type
Original Paper
Information
Psychometrika , Volume 64 , Issue 1 , March 1999 , pp. 69 - 82
Copyright
Copyright © 1999 The Psychometric Society

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Footnotes

We thank Michael Newton and Daode Huang for their helpful comments and suggestions.

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