Exact unconditional testing procedures for comparing two independent Poisson rates
Journal of Statistical Computation and Simulation
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We consider seven exact unconditional testing procedures for comparing adjusted incidence rates between two groups from a Poisson process. Exact tests are always preferable due to the guarantee of test size in small to medium sample settings. Han [Comparing two independent incidence rates using conditional and unconditional exact tests. Pharm Stat. 2008;7(3):195–201] compared the performance of partial maximization p-values based on the Wald test statistic, the likelihood ratio test statistic, the score test statistic, and the conditional p-value. These four testing procedures do not perform consistently, as the results depend on the choice of test statistics for general alternatives. We consider the approach based on estimation and partial maximization, and compare these to the ones studied by Han (2008) for testing superiority. The procedures are compared with regard to the actual type I error rate and power under various conditions. An example from a biomedical research study is provided to illustrate the testing procedures. The approach based on partial maximization using the score test is recommended due to the comparable performance and computational advantage in large sample settings. Additionally, the approach based on estimation and partial maximization performs consistently for all the three test statistics, and is also recommended for use in practice.
Clinical trials; Exact test; E+M p-value; Poisson; Poisson distribution; Poisson processes; Power; Statistics; Unconditional test
Clinical Trials | Medicine and Health Sciences | Statistical Models | Statistics and Probability | Vital and Health Statistics
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Exact unconditional testing procedures for comparing two independent Poisson rates.
Journal of Statistical Computation and Simulation, 85(5),