Document Type

Journal Article

Department/Unit

Department of Mathematics

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.

Publication Year

2010

Journal Title

Journal of Statistical Computation and Simulation

Volume number

80

Issue number

3

Publisher

Taylor & Francis

First Page (page number)

263

Last Page (page number)

271

Referreed

1

DOI

10.1080/00949650802609475

ISSN (print)

1563-5163

Link to Publisher’s Edition

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

Keywords

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

Included in

Mathematics Commons

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