On non-parametric and generalized tests for the two-sample problem with location and scale change alternatives.

M J Podgor; J L Gastwirth

doi:10.1002/sim.4780130535

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On non-parametric and generalized tests for the two-sample problem with location and scale change alternatives.

M J Podgor·J L Gastwirth

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Abstract

Various tests have been proposed for the two-sample problem when the alternative is more general than a simple shift in location: non-parametric tests; O'Brien's generalized t and rank sum tests; and other tests related to the t. We show that the generalized tests are directly related to non-parametric tests proposed by Lepage. As a result, we obtain a wider, more flexible class of O'Brien-type procedures which inherit the level robustness property of non-parametric tests. We have also computed the tests' empirical sizes and powers under several models. The non-parametric procedures and the related O'Brien-type tests are valid and yield good power in the settings investigated. They are preferable to the t-test and related procedures whose type I errors differ noticeably from nominal size for skewed and long-tailed distributions.

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Clinical Trials as Topic Computer Simulation Data Interpretation, Statistical Diabetic Neuropathies Humans Models, Statistical Normal Distribution Pain Measurement Regression Analysis Treatment Outcome Journal Article Research Support, U.S. Gov't, Non-P.H.S.

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M J Podgor, J L Gastwirth. On non-parametric and generalized tests for the two-sample problem with location and scale change alternatives.. https://doi.org/10.1002/sim.4780130535

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