Abstract #301148

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JSM 2003 Abstract #301148
Activity Number: 226
Type: Invited
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #301148
Title: A General Censoring Model for Stochastic Processes and Conditions of Ignorability for Multistate Models
Author(s): Daniel Commenges*+
Companies: ISPED
Address: Université Victor Segalen Bordeaux 2, Bordeaux, Cedex, , F-33076, France
Keywords: censoring ; coarsening ; stochastic process ; ignorability ; multistate
Abstract:

A general model for censoring is the following. Consider a possibily multivariate stochastic process X(t). Inference about its law must be based on observations but it is rare that X(t) is observed for all t. We represent the mechanism of observation by a process R(t) which takes values 0 or 1: X(t) is observed if R(t)=1, not observed if R(t)=0. If X is multivariate, we may also consider R as multivariate. If R is fixed, the observed likelihood can in general be written relatively simply. If R is a stochastic process, the question is whether we will do the same inference, writing the likelihood as if R was fixed or writing the full likelihood; this is the question of ignorability of the mechanism leading to missing observations. It is proved in a paper submitted to publication that the coarsening mechanism is ignorable if R is independent of X given the observed values of X. Implications for inference in multistate models and examples, including double censoring, will be given.

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