title: How to test hypotheses if you must.
abstract: 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.
authors: ICON Adaptive Trials Innovation Centre, Icon Plc, Marlow, Buckinghamshire, UK.
authors: Andrew P
authors: AP
authors: Grieve
mesh_terms: D001499:Bayes Theorem; D003627:Data Interpretation, Statistical; D055808:Drug Discovery / Q000379:methods* / Q000706:statistics & numerical data*; D006801:Humans; D018401:Sample Size
keywords: Bayesian test; Lindley's paradox; Neyman-Pearson lemma; hypothesis tests; likelihood principle; null hypothesis significance tests; planning of experiments; power; sample sizing; sampling frame; type I error; type II error