Linear transformation models for survival analysis with tumor growth information in cancer screening study - Shen, Pao-Sheng (Communications in statistics. Theory and methods, 2017)
The complication in analyzing tumor data is that the tumors detected in a screening program tend to be slowly progressive tumors, which is the so-called left-truncated sampling that is inherent in screening studies. Under the assumption that all subjects have the same tumor growth function, Ghosh ( 2008 ) developed estimation procedures for the Cox proportional hazards model. Shen ( 2011a ) demonstrated that Ghosh ( 2008 )'s approach can be extended to the case when each subject has a specific growth function. In this article, under linear transformation model, we present a general framework to the analysis of data from cancer screening studies. We developed estimation procedures under linear transformation model, which includes Cox's model as a special case. A simulation study is conducted to demonstrate the potential usefulness of the proposed estimators.