Literature DB >> 23255195

Seven myths of randomisation in clinical trials.

Stephen Senn1.   

Abstract

I consider seven misunderstandings that may be encountered about the nature, purpose and properties of randomisation in clinical trials. Some concern the practical realities of clinical research on patients. Others are to do with the value and purpose of balance. Still others are to do with a confusion about the role of conditioning in valid statistical inference. I consider a simple game of chance involving two dice to illustrate some points about inference and then consider the seven misunderstandings in turn. I conclude that although one should not make a fetish of randomisation, when proposing alternatives to randomisation in clinical trials, one should be very careful to be precise about the exact nature of the alternative being considered if one is to avoid the danger of underestimating the advantages that randomisation can offer.
Copyright © 2012 John Wiley & Sons, Ltd.

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Year:  2012        PMID: 23255195     DOI: 10.1002/sim.5713

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


  30 in total

1.  Limitations of individual causal models, causal graphs, and ignorability assumptions, as illustrated by random confounding and design unfaithfulness.

Authors:  Sander Greenland; Mohammad Ali Mansournia
Journal:  Eur J Epidemiol       Date:  2015-02-17       Impact factor: 8.082

2.  The Confounding Question of Confounding Causes in Randomized Trials.

Authors:  Jonathan Fuller
Journal:  Br J Philos Sci       Date:  2018-01-22       Impact factor: 3.978

3.  Statistical properties of minimal sufficient balance and minimization as methods for controlling baseline covariate imbalance at the design stage of sequential clinical trials.

Authors:  Steven D Lauzon; Viswanathan Ramakrishnan; Paul J Nietert; Jody D Ciolino; Michael D Hill; Wenle Zhao
Journal:  Stat Med       Date:  2020-05-04       Impact factor: 2.373

4.  Evaluation of Differences in Individual Treatment Response in Schizophrenia Spectrum Disorders: A Meta-analysis.

Authors:  Stephanie Winkelbeiner; Stefan Leucht; John M Kane; Philipp Homan
Journal:  JAMA Psychiatry       Date:  2019-10-01       Impact factor: 21.596

5.  Managing competing demands in the implementation of response-adaptive randomization in a large multicenter phase III acute stroke trial.

Authors:  Wenle Zhao; Valerie Durkalski
Journal:  Stat Med       Date:  2014-05-22       Impact factor: 2.373

Review 6.  Some common misperceptions about P values.

Authors:  Yuko Y Palesch
Journal:  Stroke       Date:  2014-11-06       Impact factor: 7.914

7.  Study Types in Orthopaedics Research: Is My Study Design Appropriate for the Research Question?

Authors:  Isabella Zaniletti; Katrina L Devick; Dirk R Larson; David G Lewallen; Daniel J Berry; Hilal Maradit Kremers
Journal:  J Arthroplasty       Date:  2022-09-06       Impact factor: 4.435

8.  Planning a method for covariate adjustment in individually randomised trials: a practical guide.

Authors:  Tim P Morris; A Sarah Walker; Elizabeth J Williamson; Ian R White
Journal:  Trials       Date:  2022-04-18       Impact factor: 2.728

9.  A randomized controlled trial comparing non-steroidal anti-inflammatory and fusion protein inhibitors singly and in combination on the histopathology of bovine respiratory syncytial virus infection.

Authors:  Francisco R Carvallo Chaigneau; Paul Walsh; Maxim Lebedev; Victoria Mutua; Heather McEligot; Heejung Bang; Laurel J Gershwin
Journal:  PLoS One       Date:  2021-06-10       Impact factor: 3.240

10.  Understanding and misunderstanding randomized controlled trials.

Authors:  Angus Deaton; Nancy Cartwright
Journal:  Soc Sci Med       Date:  2017-12-25       Impact factor: 5.379

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