Parametric bootstrap and approximate tests for two Poisson variates

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)263-271
Number of pages9
JournalJournal of Statistical Computation and Simulation
Volume80
Issue number3
DOIs
Publication statusPublished - Mar 2010

Scopus Subject Areas

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

User-Defined Keywords

  • Asymptotic tests
  • Monte Carlo tests
  • Parametric bootstrap
  • Poisson process
  • Rate ratio

Fingerprint

Dive into the research topics of 'Parametric bootstrap and approximate tests for two Poisson variates'. Together they form a unique fingerprint.

Cite this