Evidence map›Paper›PMID 34369220›Full record

ArticleStatistical methods in medical research2021

The change in estimate method for selecting confounders: A simulation study.

Denis Talbot, Awa Diop, Mathilde Lavigne-Robichaud, Chantal Brisson

Abstract read
In one paragraph

Article in Statistical methods in medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–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

21 citing papers in PubMed.

  1. Article
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  3. Collapsibility in case-control studies.International journal of epidemiology · 2026
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  15. Correlations between weight perception and overt risk-taking among Canadian adolescents.Canadian journal of public health = Revue canadienne de sante publique · 2023
    Article
  16. Article
  17. Consumption and Breakfast Patterns in Children and Adolescents with Congenital Heart Disease.International journal of environmental research and public health · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Denis TalbotDépartement de médecine sociale et préventive, Université Laval, Québec, Canada.ORCID 0000-0003-0431-3314
Awa DiopDépartement de médecine sociale et préventive, Université Laval, Québec, Canada.
Mathilde Lavigne-RobichaudDépartement de médecine sociale et préventive, Université Laval, Québec, Canada.ORCID 0000-0002-5130-9118
Chantal BrissonDépartement de médecine sociale et préventive, Université Laval, Québec, Canada.

Funding

CIHR
6 · The paper itself

Abstract

backgroundThe change in estimate is a popular approach for selecting confounders in epidemiology. It is recommended in epidemiologic textbooks and articles over significance test of coefficients, but concerns have been raised concerning its validity. Few simulation studies have been conducted to investigate its performance.

methodsAn extensive simulation study was realized to compare different implementations of the change in estimate method. The implementations were also compared when estimating the association of body mass index with diastolic blood pressure in the PROspective Québec Study on Work and Health.

resultsAll methods were susceptible to introduce important bias and to produce confidence intervals that included the true effect much less often than expected in at least some scenarios. Overall mixed results were obtained regarding the accuracy of estimators, as measured by the mean squared error. No implementation adequately differentiated confounders from non-confounders. In the real data analysis, none of the implementation decreased the estimated standard error.

conclusionBased on these results, it is questionable whether change in estimate methods are beneficial in general, considering their low ability to improve the precision of estimates without introducing bias and inability to yield valid confidence intervals or to identify true confounders.

Indexed as

Research DesignBiasComputer SimulationProspective StudiesConfoundingepidemiologic methodsmodelingvariable selection

Identifiers

PMID34369220
PMCPMC8424612

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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.