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General partially linear varying-coefficient transformation model with right censored data. (English) Zbl 1242.62111

Summary: A unified maximum marginal likelihood estimation procedure is proposed for the analysis of right censored data using general partially linear varying-coefficient transformation models (GPLVCTM), which are flexible enough to include many survival models as its special cases. Unknown functional coefficients in the models are approximated by cubic B-spline polynomials. We estimate the B-spline coefficients and regression parameters by maximizing the marginal likelihood function. One advantage of this procedure is that it is free of both baseline and censoring distributions. Through simulation studies and a real data application (VA data from the Veteran’s Administration Lung Cancer Study Clinical Trial), we illustrate that the proposed estimation procedure is accurate, stable and practical.

MSC:

62N01 Censored data models
62N02 Estimation in survival analysis and censored data
62J05 Linear regression; mixed models
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