4.2 Article

How to test hypotheses if you must

期刊

PHARMACEUTICAL STATISTICS
卷 14, 期 2, 页码 139-150

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WILEY
DOI: 10.1002/pst.1667

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hypothesis tests; null hypothesis significance tests; type I error; type II error; power; planning of experiments; sample sizing; Neyman-Pearson lemma; likelihood principle; sampling frame; Lindley's paradox; Bayesian test

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Drug development is not the only industrial-scientific enterprise subject to government regulations. In some fields of ecology and environmental sciences, the application of statistical methods is also regulated by ordinance. Over the past 20years, ecologists and environmental scientists have argued against an unthinking application of null hypothesis significance tests. More recently, Canadian ecologists have suggested a new approach to significance testing, taking account of the costs of both type I and type II errors. In this paper, we investigate the implications of this for testing in drug development and demonstrate that its adoption leads directly to the likelihood principle and Bayesian approaches. Copyright (c) 2015 John Wiley & Sons, Ltd.

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