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Biometrika 1977 64(2):215-224; doi:10.1093/biomet/64.2.215
© 1977 by Biometrika Trust
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Models for censored survival analysis: Constant-sum and variable-sum models

J. S. WILLIAMS and S. W. LAGAKOS

Department of Statistics, Colorado State University Fort Collins
Statistical Science Division, State University of New York Buffalo

In the analysis of survival-type variables arising from medical investigations, one is often faced with incomplete or right-censored observations. In many cases the mechanisms leading to censoring are intrinsically related to the survival variable and standard methods of analysis are not appropriate. In this paper we examine consequences of the dependence of survival on the causes of censoring. Also examined are the testability of a set of data for the importance in survival inferences of the underlying censoring mechanism as well as the consequences of falsely assuming that the censoring mechanism does not affect inferences about survival. The special case in which survival is exponential is discussed in detail.

Key Words: Censored survival data • Clinical trial • Exponential distribution • Identifiability


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