Abstract #301583

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JSM 2003 Abstract #301583
Activity Number: 423
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #301583
Title: Bootstrap Adjustment of the Asymptotic Normal Tests for Animal Carcinogenicity Data
Author(s): Hojin Moon*+ and Hongshik Ahn and Ralph L. Kodell
Companies: Food and Drug Administration and SUNY at Stony Brook and NCTR/Food and Drug Administration
Address: 3900 NCTR Rd., HFT- 20, Jefferson, AR, 72079,
Keywords: dose response ; sacrifice ; trend test ; tumorigenicity
Abstract:

We develop a bootstrap resampling method for improving the asymptotic normal tests for animal carcinogenicity data. The proposed bootstrap resampling method differs from conventional bootstrap methods in the aspect of preserving the mortality rate in each dose group under the null hypothesis of equal tumor incidence rates among the groups. The asymptotic normal distribution of the test statistic is often invalid in certain dose response trend tests. For instance, the survival-adjusted Cochran Armitage test, known to be the Poly-k test, is asymptotically standard normal under the null hypothesis. However, the asymptotic normality is not valid if there is a discrepancy in the tumor onset distribution that is assumed in this test. We investigate an empirical distribution of the trend test using the proposed bootstrap resampling method and compare it with the standard normal distribution. A simulation study is conducted to evaluate the robustness of the test to various tumor onset distributions.

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