Cox regression for mixed case interval-censored data with covariate errors

Covariate measurement error problems have been extensively studied in the context of right-censored data but less so for interval-censored data. Motivated by the AIDS Clinical Trial Group 175 study, where the occurrence time of AIDS was examined only at intermittent clinic visits and the baseline covariate CD4 count was measured with error, we describe a semiparametric maximum likelihood method for analyzing mixed case interval-censored data with mismeasured covariates under the proportional hazards model. We show that the estimator of the regression coefficient is asymptotically normal and efficient and provide a very stable and efficient algorithm for computing the estimators. We evaluate the method through simulation studies and illustrate it with AIDS data.