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A latent variable model for discrete multivariate psychometric waiting times. (English) Zbl 1291.62202

Summary: 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.

MSC:

62P15 Applications of statistics to psychology
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