Literature DB >> 31406387

The Confounding Question of Confounding Causes in Randomized Trials.

Jonathan Fuller1,2.   

Abstract

It is sometimes thought that randomized study group allocation is uniquely proficient at producing comparison groups that are evenly balanced for all confounding causes. Philosophers have argued that in real randomized controlled trials this balance assumption typically fails. But is the balance assumption an important ideal? I run a thought experiment, the CONFOUND study, to answer this question. I then suggest a new account of causal inference in ideal and real comparative group studies that helps clarify the roles of confounding variables and randomization. 1Confounders and Causes2The Balance Assumption3The CONFOUND Study 3.1CONFOUND 13.2CONFOUND 24Disjunction C and the Ideal Study 4.1The ultimate 'other cause': C4.2The ideal comparative group study4.3Required conditions for causal inference5Confounders as Causes, Confounders as Correlates6Summary.

Year:  2018        PMID: 31406387      PMCID: PMC6686148          DOI: 10.1093/bjps/axx015

Source DB:  PubMed          Journal:  Br J Philos Sci        ISSN: 0007-0882            Impact factor:   3.978


  11 in total

1.  History of the modern epidemiological concept of confounding.

Authors:  Alfredo Morabia
Journal:  J Epidemiol Community Health       Date:  2010-08-09       Impact factor: 3.710

2.  Causation and causal inference in epidemiology.

Authors:  Kenneth J Rothman; Sander Greenland
Journal:  Am J Public Health       Date:  2005       Impact factor: 9.308

3.  Why randomized interventional studies.

Authors:  Adam La Caze
Journal:  J Med Philos       Date:  2013-08

4.  Hume, Mill, Hill, and the sui generis epidemiologic approach to causal inference.

Authors:  Alfredo Morabia
Journal:  Am J Epidemiol       Date:  2013-09-26       Impact factor: 4.897

5.  What does randomisation achieve?

Authors:  Adam La Caze; Benjamin Djulbegovic; Stephen Senn
Journal:  Evid Based Med       Date:  2011-06-21

6.  Evaluating Ebola therapies--the case for RCTs.

Authors:  Edward Cox; Luciana Borio; Robert Temple
Journal:  N Engl J Med       Date:  2014-12-03       Impact factor: 91.245

7.  Seven myths of randomisation in clinical trials.

Authors:  Stephen Senn
Journal:  Stat Med       Date:  2012-12-17       Impact factor: 2.373

8.  Selection of patients for randomized controlled trials: implications of wide or narrow eligibility criteria.

Authors:  S Yusuf; P Held; K K Teo; E R Toretsky
Journal:  Stat Med       Date:  1990 Jan-Feb       Impact factor: 2.373

Review 9.  Threats to applicability of randomised trials: exclusions and selective participation.

Authors:  A Britton; M McKee; N Black; K McPherson; C Sanderson; C Bain
Journal:  J Health Serv Res Policy       Date:  1999-04

10.  The Risk GP Model: the standard model of prediction in medicine.

Authors:  Jonathan Fuller; Luis J Flores
Journal:  Stud Hist Philos Biol Biomed Sci       Date:  2015-07-26
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  2 in total

Review 1.  Design and conduct of confirmatory chronic pain clinical trials.

Authors:  Nathaniel Katz
Journal:  Pain Rep       Date:  2020-12-18

2.  E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance.

Authors:  Francesco De Pretis; Jürgen Landes; Barbara Osimani
Journal:  Front Pharmacol       Date:  2019-12-17       Impact factor: 5.810

  2 in total

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