Morris, TP;
Kahan, BC;
White, IR;
(2014)
Choosing sensitivity analyses for randomised trials: principles.
BMC Medical Research Methodology
, 14
(1)
, Article 11. 10.1186/1471-2288-14-11.
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Abstract
Background Sensitivity analyses are an important tool for understanding the extent to which the results of randomised trials depend upon the assumptions of the analysis. There is currently no guidance governing the choice of sensitivity analyses. Discussion We provide a principled approach to choosing sensitivity analyses through the consideration of the following questions: 1) Does the proposed sensitivity analysis address the same question as the primary analysis? 2) Is it possible for the proposed sensitivity analysis to return a different result to the primary analysis? 3) If the results do differ, is there any uncertainty as to which will be believed? Answering all of these questions in the affirmative will help researchers to identify relevant sensitivity analyses. Treating analyses as sensitivity analyses when one or more of the answers are negative can be misleading and confuse the interpretation of studies. The value of these questions is illustrated with several examples. Summary By removing unreasonable analyses that might have been performed, these questions will lead to relevant sensitivity analyses, which help to assess the robustness of trial results.
Type: | Article |
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Title: | Choosing sensitivity analyses for randomised trials: principles |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1186/1471-2288-14-11 |
Publisher version: | http://dx.doi.org/10.1186/1471-2288-14-11 |
Language: | English |
Additional information: | © 2014 Morris et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Sensitivity analysis, randomised trials, clinical trials, RCT, missing data |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1419319 |
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