Bivariate Latent Variable Models for Clustered Discrete and Continuous Outcomes
聚类离散与连续结局的双变量潜变量模型
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…