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Erschienen in:
2010 | OriginalPaper | Buchkapitel
17. Efficient Regression Estimation Under General Censoring and Truncation
verfasst von : Catherine Huber
Erschienen in: Mathematical and Statistical Models and Methods in Reliability
Verlag: Birkhäuser Boston
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Abstract
Much attention has been paid to the semi-parametric approach for right censored data in survival analysis while the case of data that are also truncated has been considered less frequently. We consider here the case of data that are censored and truncated in the most general way and obtain an efficient estimator of a regression model relying on a basic hazard that is non parametric. The model is defined in Sect. 17.1, the censorship and truncation scheme is described in Sect. 17.2. The resulting model for the really observed data is derived in Sect. 17.3 and the efficiency of the proposed estimator proved in Sect. 17.4. The last section deals with commentaries and perspectives of this work which was conducted in collaboration with Valentin Solev of the Steklov Institute in Saint Petersbourg (Russia) and Filia Vonta of the National Technical University in Athens (Greece).