Document Type

Journal Article

Department/Unit

Department of Mathematics

Language

English

Abstract

The parametric bootstrap tests and the asymptotic or approximate tests for detecting difference of two Poisson means are compared. The test statistics used are the Wald statistics with and without log-transformation, the Cox F statistic and the likelihood ratio statistic. It is found that the type I error rate of an asymptotic/approximate test may deviate too much from the nominal significance level α under some situations. It is recommended that we should use the parametric bootstrap tests, under which the four test statistics are similarly powerful and their type I error rates are all close to α. We apply the tests to breast cancer data and injurious motor vehicle crash data.

Keywords

asymptotic tests, Monte Carlo tests, parametric bootstrap, Poisson process, rate ratio

Publication Date

2010

Source Publication Title

Journal of Statistical Computation and Simulation

Volume

80

Issue

3

Start Page

263

End Page

271

Publisher

Taylor & Francis

Peer Reviewed

1

DOI

10.1080/00949650802609475

Link to Publisher's Edition

http://dx.doi.org/10.1080/00949650802609475

ISSN (print)

15635163

Included in

Mathematics Commons

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