REGRESSION ANALYSIS OF MULTIVARIATE CURRENT STATUS DATA WITH SEMIPARAMETRIC TRANSFORMATION FRAILTY MODELS

摘要

This study investigates regression analysis of multivariate current status data using a class of flexible semiparametric transformation frailty models. The maximum likelihood estimation procedure is derived for the problem. In particular, a novel EM algorithm, which is quite stable and can be easily implemented, is developed. In addition, the asymptotic properties of the resulting estimators are established, and a numerical study indicates that the proposed methodology works well in practical situations. An application is provided to illustrate the proposed method.