Likelihood Inference in a Correlated Probit Regression Model
相关 Probit 回归模型的似然推断
Equicorrelated binary observations are modelled using a multivariate probit regression model. Log likelihood derivatives are reduced to simple linear combinations of equicorrelated multivariate normal probabilities, which are approximated using the method of Mendell & Elston (1974). A data set with overdispersion illustrates the use of this model.