Efficient inferences for linear transformation models with doubly censored data
Efficient inferences for linear transformation models with doubly censored data
Doubly-censored data, which consist of exact and case-1 interval-censored observations, often arise in medical studies, such as HIV/AIDS clinical trials. This article considers nonparametric maximum likelihood estimation (NPMLE) of semiparametric transformation models that encompass the proportional hazards and proportional odds models when data are subject to double censoring. The maximum …