Abstract #300402

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JSM 2003 Abstract #300402
Activity Number: 422
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #300402
Title: Bootstrap Approximations in Model Checks for Binary Data
Author(s): Gerhard Dikta*+
Companies: FH-Aachen, University of Applied Sciences
Address: Gerhard Dikta, Paderborn, D-33100, Germany
Keywords: goodness of fit ; binary data analysis ; bootstrap ; random censorship model ; marked empirical ; semiparametric estimation
Abstract:

Consider a binary regression model, where the conditional expectation of the binary variable given an explanatory variable belongs to a parametric family. To check whether a sequence of independent and identically distributed observations of these variables belongs to such a parametric family, we use Kolmogorov-Smirnov and Cramer von Mises type tests which are based on maximum likelihood estimation of the parameter and on a marked empirical process introduced by Stute. We study a new resampling scheme of the bootstrap in this setup to approximate the critical values belonging to these tests. Furthermore, this approach is applied to simulated and real data. In the latter case we check whether a certain semiparametric random censorship model introduced by Dikta is applicable to some right censored datasets.

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