Literature DB >> 2218164

Must clinical trials be large? The interpretation of P-values and the combination of test results.

G A Barnard1.   

Abstract

The notion that small, well planned clinical trials may not be worth undertaking is shown to arise from an overemphasis on just one way of interpreting P-values. Alternative forms of P and other interpretations are put forward. Attention is drawn to some aspects of the theory of hypothesis testing which seem less well known than they should be.

Mesh:

Year:  1990        PMID: 2218164     DOI: 10.1002/sim.4780090606

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  A statistical method for studying correlated rare events and their risk factors.

Authors:  Xiaonan Xue; Mimi Y Kim; Tao Wang; Mark H Kuniholm; Howard D Strickler
Journal:  Stat Methods Med Res       Date:  2015-04-08       Impact factor: 3.021

2.  Validation of ITD mutations in FLT3 as a therapeutic target in human acute myeloid leukaemia.

Authors:  Catherine C Smith; Qi Wang; Chen-Shan Chin; Sara Salerno; Lauren E Damon; Mark J Levis; Alexander E Perl; Kevin J Travers; Susana Wang; Jeremy P Hunt; Patrick P Zarrinkar; Eric E Schadt; Andrew Kasarskis; John Kuriyan; Neil P Shah
Journal:  Nature       Date:  2012-04-15       Impact factor: 49.962

3.  Meta-Analysis of Mid-p-Values: Some New Results based on the Convex Order.

Authors:  Patrick Rubin-Delanchy; Nicholas A Heard; Daniel J Lawson
Journal:  J Am Stat Assoc       Date:  2018-08-06       Impact factor: 5.033

  3 in total

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