A latent variable model for discrete multivariate psychometric waiting times

Jeffrey A. Douglas, Michael R. Kosorok, Betty A. Chewning

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)69-82
Number of pages14
Issue number1
StatePublished - Mar 1999
Externally publishedYes


  • Frailty
  • Latent variable
  • Metropolis-hastings algorithm
  • Survival analysis

ASJC Scopus subject areas

  • Mathematics (miscellaneous)
  • Psychology(all)
  • Psychology (miscellaneous)
  • Social Sciences (miscellaneous)


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