ArticleInternational journal of epidemiology2022
E-values for effect heterogeneity and approximations for causal interaction.
Article in International journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Time to Benefit of Surgery vs Targeted Medical Therapy for Patients With Primary Aldosteronism: A Meta-analysis.The Journal of clinical endocrinology and metabolism · 2024Pooled it
- Body mass index and hospital mortality in mechanically ventilated patients with acute hypoxaemic respiratory failure: A retrospective cohort study.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2026Article
- Individualised treatment effects of corticosteroids in IgA nephropathy.EBioMedicine · 2026Article
- Variation in Long-Term Postoperative Mortality Risk by Race/Ethnicity After Major Non-cardiac Surgeries in the Veterans Health Administration.Journal of racial and ethnic health disparities · 2025Article
- Cardiovascular disease risk associated with housing disadvantages among middle-aged and older populations in China: a cohort study.BMC public health · 2025Article
- Article
- Heterogeneity in the effect of type 2 diabetes on dementia incidence in a diverse cohort of Asian American and non-Latino White older adults.American journal of epidemiology · 2024Article
- Exploring a Potential Interaction Between the Effect of Specific Maternal Smoking Patterns and Comorbid Antenatal Depression in Causing Postpartum Depression.Neuropsychiatric disease and treatment · 2024Article
- Sensitivity analysis for the interactive effects of internal bias and publication bias in meta-analyses.Research synthesis methods · 2024Article
- The M-Value: A Simple Sensitivity Analysis for Bias Due to Missing Data in Treatment Effect Estimates.American journal of epidemiology · 2023Article
Corrections and comments
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Authors and funding
5 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundEstimates of effect heterogeneity (i.e. the extent to which the causal effect of one exposure varies across strata of a second exposure) can be biased if the exposure-outcome relationship is subject to uncontrolled confounding whose severity differs across strata of the second exposure.
methodsWe propose methods, analogous to the E-value for total effects, that help to assess the sensitivity of effect heterogeneity estimates to possible uncontrolled confounding. These E-value analogues characterize the severity of uncontrolled confounding strengths that would be required, hypothetically, to 'explain away' an estimate of multiplicative or additive effect heterogeneity in the sense that appropriately controlling for those confounder(s) would have shifted the effect heterogeneity estimate to the null, or alternatively would have shifted its confidence interval to include the null. One can also consider shifting the estimate or confidence interval to an arbitrary non-null value. All of these E-values can be obtained using the R package EValue.
resultsWe illustrate applying the proposed E-value analogues to studies on: (i) effect heterogeneity by sex of the effect of educational attainment on dementia incidence and (ii) effect heterogeneity by age on the effect of obesity on all-cause mortality.
conclusionReporting these proposed E-values could help characterize the robustness of effect heterogeneity estimates to potential uncontrolled confounding.
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