Semiparametric Regression Models for Repeated Events with Random Effects and Measurement Error
含随机效应与测量误差的重复事件半参数回归
Statistical methodology is presented for the regression analysis of multiple events in the presence of random effects and measurement error. Omitted covariates are modeled as random effects. Our approach to parameter estimation and significance testing is to start with a naive model of semiparametric Poisson process regression, and then to adjust for random effects and any possible covariate measurement error. We illustrate the techniques with data from a randomized clinical…