标题： 具有混合二值和连续响应变量的潜在变量模型 显示英文标题

标题： A latent variable model with mixed binary and continuous response variables

摘要： 我们提出了一种在既有连续又有二元结果的模型中获得最大似然估计的方法。左删失和右删失观测值的组合在这种框架下也可以自然地建模。该模型及其估计程序已在 R 包 lava.tobit 中实现。该方法通过脑成像和人格数据进行演示，在这种数据中，预测变量的测量误差是在潜在变量框架下处理的。还进行了一个模拟研究，比较了小样本下最大似然估计与有限信息估计量的小样本特性。 显示英文摘要

摘要： We propose a method for obtaining maximum likelihood estimates in a model with continuous and binary outcomes. Combinations of left and right censored observations are also naturally modeled in this framework. The model and estimation procedure has been implemented in the R package lava.tobit. The method is demonstrated on brain imaging and personality data where measurement error on predictor variables is handled in a latent variable framework. A simulation study is conducted comparing the small sample properties of the MLE with a limited information estimator.