Bivariate Latent Variable Models for Clustered Discrete and Continuous Outcomes
作者:
PaulJ. Catalano,
LouiseM. Ryan,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1992)
卷期:
Volume 87,
issue 419
页码: 651-658
ISSN:0162-1459
年代: 1992
DOI:10.1080/01621459.1992.10475264
出版商: Taylor & Francis Group
关键词: Developmental toxicity;Linear model;Litter effects;Probit model;Quasi-likelihood;Random effects
数据来源: Taylor
摘要:
We use the concept of a latent variable to derive the joint distribution of a continuous and a discrete outcome, and then extend the model to allow for clustered data. The model can be parameterized in a way that allows one to write the joint distribution as a product of a standard random effects model for the continuous variable and a correlated probit model for the discrete variable. This factorization suggests a convenient approach to parameter estimation using quasi-likelihood techniques. Our approach is motivated by the analysis of developmental toxicity experiments for which a number of discrete and continuous outcomes are measured on offspring clustered within litters. Fetal weight and malformation data illustrate the results.
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