Testing the ratio of two poisson rates.
In this paper we compare the properties of four different general approaches for testing the ratio of two Poisson rates. Asymptotically normal tests, tests based on approximate p -values, exact conditional tests, and a likelihood ratio test are considered. The properties and power performance of these tests are studied by a Monte Carlo simulation experiment. Sample size calculation formulae are given for each of the test procedures and their validities are studied. Some recommendations favoring the likelihood ratio and certain asymptotic tests are based on these simulation results. Finally, all of the test procedures are illustrated with two real life medical examples.
Gu
Kangxia
K
Department of Statistical Science, Southern Methodist University, 3225 Daniel Avenue PO Box 750332, Dallas, Texas 75275-0332, USA.
Ng
Hon Keung Tony
HK
Tang
Man Lai
ML
Schucany
William R
WR
D001943:Breast Neoplasms / Q000453:epidemiology; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D006801:Humans; D016013:Likelihood Functions; D009010:Monte Carlo Method; D016012:Poisson Distribution; D018401:Sample Size