Likelihood Inference in a Correlated Probit Regression Model
该文用多元Probit回归模型处理等相关二元观测数据，将对数似然导数简化为等相关多元正态概率的线性组合，并用Mendell-Elston方法近似，最后用过度离散数据集演示模型应用。
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.