Displaying similar documents to “Some aspects of the conditional inference when the sample size is random.”

The behavior of locally most powerful tests

Marek Omelka (2005)

Kybernetika

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The locally most powerful (LMP) tests of the hypothesis H : θ = θ 0 against one-sided as well as two-sided alternatives are compared with several competitive tests, as the likelihood ratio tests, the Wald-type tests and the Rao score tests, for several distribution shapes and for location, shape and vector parameters. A simulation study confirms the importance of the condition of local unbiasedness of the test, and shows that the LMP test can sometimes dominate the other tests only in a very restricted...

Sample size determination in the Mann–Whitney test

Andrzej Kornacki, Andrzej Bochniak, Agnieszka Kubik-Komar (2017)

Biometrical Letters

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This paper discusses the problem of determining the number of observations necessary to apply the nonparametric Mann-Whitney test. We describe the method given by Noether (1987) for determining a sample size which guarantees that the Mann-Whitney test at a given significance level α has a predetermined power 1-β. The presented theory is tested by calculating the empirical power in computer simulations. The paper also raises the issue of the method of rounding the determined sample size...

Power comparison of Rao′s score test, the Wald test and the likelihood ratio test in (2xc) contingency tables

Anita Dobek, Krzysztof Moliński, Ewa Skotarczak (2015)

Biometrical Letters

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There are several statistics for testing hypotheses concerning the independence of the distributions represented by two rows in contingency tables. The most famous are Rao′s score, the Wald and the likelihood ratio tests. A comparison of the power of these tests indicates the Wald test as the most powerful.