How to test hypotheses if you must

Pharmaceutical Statistics

Volumn 14, Issue 2, 2015, Pages 139-150

  Grieve, Andrew P ^a  

^a ICON PLC   (United Kingdom)

Author keywords

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

Indexed keywords

ARTICLE; BAYES THEOREM; DRUG DEVELOPMENT; NULL HYPOTHESIS; PROBABILITY; SAMPLE SIZE; STATISTICAL SIGNIFICANCE; HUMAN; PROCEDURES; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA;

BAYES THEOREM; DATA INTERPRETATION, STATISTICAL; DRUG DISCOVERY; HUMANS; SAMPLE SIZE;

EID: 84925634275     PISSN: 15391604     EISSN: 15391612     Source Type: Journal    
DOI: 10.1002/pst.1667     Document Type: Article

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