Matching conditional and marginal shapes in binary random intercept models using a bridge distribution function
用桥接分布匹配二元随机截距模型的条件与边际函数形式
SUMMARY Random effects logistic regression models are often used to model clustered binary response data. Regression parameters in these models have a conditional, subject-specific interpretation in that they quantify regression effects for each cluster. Very often, the logistic functional shape conditional on the random effects does not carry over to the marginal scale. Thus, parameters in these models usually do not have an explicit marginal, population-averaged…