Evidence map›Paper›PMID 24456267›Full record

ArticleBMC medical research methodology2014

Choosing sensitivity analyses for randomised trials: principles.

Tim P Morris, Brennan C Kahan, Ian R White

Abstract read
In one paragraph

Article in BMC medical research methodology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  5. Estimands for factorial trials.Statistics in medicine · 2022
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  13. The Role of Analysis Populations and Estimands in Clinical Trials.Journal of the American Society of Nephrology : JASN · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Tim P MorrisHub for Trials Methodology Research, MRC Clinical Trials Unit at UCL, Aviation House, 125 Kingsway, London WC2B 6NH, UK. tim.morris@ucl.ac.uk.
Brennan C Kahan
Ian R White

Funding

Medical Research Council MC_EX_G0800814Medical Research Council MC_U105260558Medical Research Council U105260558
6 · The paper itself

Abstract

backgroundSensitivity 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.

Indexed as

Research DesignData CollectionHumansMulticenter Studies as TopicOutcome Assessment, Health CareRandomized Controlled Trials as Topic

Identifiers

PMID24456267
PMCPMC3904008

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.