Evidence map›Paper›PMID 33682654›Full record

ArticlePsychological medicine2021

Causal inference with observational data: the need for triangulation of evidence.

Gemma Hammerton, Marcus R Munafò

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Psychological medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 133 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
133citing papers in PubMed, 10 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

133 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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  3. Health-related outcomes of youth sport participation: a systematic review and meta-analysis.The international journal of behavioral nutrition and physical activity · 2025
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  14. Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
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73 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Gemma HammertonPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Marcus R MunafòMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.ORCID 0000-0002-4049-993X

Funding

Medical Research Council MC_UU_00011/7Wellcome TrustWellcome Trust 209138/Z/17/Z
6 · The paper itself

Abstract

The goal of much observational research is to identify risk factors that have a causal effect on health and social outcomes. However, observational data are subject to biases from confounding, selection and measurement, which can result in an underestimate or overestimate of the effect of interest. Various advanced statistical approaches exist that offer certain advantages in terms of addressing these potential biases. However, although these statistical approaches have different underlying statistical assumptions, in practice they cannot always completely remove key sources of bias; therefore, using design-based approaches to improve causal inference is also important. Here it is the design of the study that addresses the problem of potential bias - either by ensuring it is not present (under certain assumptions) or by comparing results across methods with different sources and direction of potential bias. The distinction between statistical and design-based approaches is not an absolute one, but it provides a framework for triangulation - the thoughtful application of multiple approaches (e.g. statistical and design based), each with their own strengths and weaknesses, and in particular sources and directions of bias. It is unlikely that any single method can provide a definite answer to a causal question, but the triangulation of evidence provided by different approaches can provide a stronger basis for causal inference. Triangulation can be considered part of wider efforts to improve the transparency and robustness of scientific research, and the wider scientific infrastructure and system of incentives.

Indexed as

CausalityObservational Studies as TopicResearch DesignBiasHumansModels, Statisticalcausal inferenceepidemiologymental healthobservational datatriangulation

Identifiers

PMID33682654
PMCPMC8020490

What OpenQuestion holds

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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.