Abstract
In ecotoxicology species reproduction tests and multiple testing of reproduction data are wide spread. While normal approximation of the data is a minor problem often the requirement of variance homogeneity is not fulfilled. Variance homogeneity is necessary to assure the proper application of statistical procedures like pairwise t tests, Dunnett t test, and Williams t test. A Poisson model can solve this issue preserving meaningful results and rendering statistical analysis more reliable. Moreover, sequential application of pairwise statistical “control vs. treatment” tests is a drawback concerning \(\alpha \)-inflation. The closure principle (CP) for hypothesis testing is used to generate a step-wise approach for detection of the No/Lowest Observed Effect Concentration using the computational approach test (CAT). The advantages and disadvantages of the combined CPCAT approach compared to the widely used t tests are pointed out and results of real data and fictitious data analysis are compared revealing the superiority of the Poisson model and CPCAT.
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