Abstract #300032

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JSM 2003 Abstract #300032
Activity Number: 178
Type: Contributed
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #300032
Title: Semiparametric Analysis for Point Process Subject to Dependent Censoring
Author(s): Mengling Liu*+
Companies: Columbia University
Address: 100 Morningside Dr., New York, NY, 10027,
Keywords: point process ; inverse probability ; cumulative baseline
Abstract:

Semiparametric transformation models are frequently applied to deal with repeatedly measured data. However, independent censoring is usually assumed for the deduction and validity of statistical method and theory. In many applications, the point process may be subject to dependent censoring caused by failure event or selective patient withdrawal. Under the assumption of conditional hazard model for dependent censoring, we develop a class of estimating equation adjusted for the dependent censoring for the baseline mean function and regression parameters. As a major feature of this article, these models offer great flexibility to formulate not only the effect of covariates on the mean function of point process, but also the dependence between the censoring and the process. Extensive simulation studies show that the proposed methods are appropriate for piratical use.

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