ReviewCurrent epidemiology reports2018
Understanding the Assumptions Underlying Instrumental Variable Analyses: a Brief Review of Falsification Strategies and Related Tools.
Review in Current epidemiology reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 7 of them syntheses that pooled 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.
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.
Who cites it
100 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Strengthening the reporting of observational studies in epidemiology using Mendelian randomization (STROBE-MR): a Korean translation of explanation and elaboration.Ewha medical journal · 2025Guideline
- Pooled it
- Alcohol consumption and its association with cancer, cardiovascular, liver and brain diseases: a systematic review of Mendelian randomization studies.Frontiers in epidemiology · 2024Pooled it
- Tools for assessing quality and risk of bias in Mendelian randomization studies: a systematic review.International journal of epidemiology · 2023Pooled it
- Separating the effects of early and later life adiposity on colorectal cancer risk: a Mendelian randomization study.BMC medicine · 2023Pooled it
- Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies.International journal of epidemiology · 2022Pooled it
- Reporting methodological issues of the mendelian randomization studies in health and medical research: a systematic review.BMC medical research methodology · 2022Pooled it
- Fluid balance control in critically ill patients: results from as-treated analyses of POINCARE-2 randomized trial.Critical care (London, England) · 2023Trial
- Migraines and the association of cognitive impairment: a one- and two-sample mendelian randomization analysis.Dialogues in clinical neuroscience · 2026Article
- Historical slavery predicts contemporary disparities in mortality between Black and White Americans.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Towards scalable biomarker discovery in posttraumatic stress disorder: triangulating genomic and phenotypic evidence from a health system biobank.Molecular psychiatry · 2026Article
- Causal Effect of Air Pollution on Outpatient Visits for Chronic Rhinitis.The Laryngoscope · 2026Article
- Understanding the effect of educational attainment on the risk of retinal detachment: a Mendelian randomization mediation analysis.International journal of retina and vitreous · 2026Article
- An approach to estimating how effective and well targeted Extreme Risk Protection Orders have been with respect to suicide prevention.American journal of epidemiology · 2026Article
- Methylphenidate Treatment and Risk of Psychotic Disorder.JAMA psychiatry · 2026Article
- Effects of the Liverpool Citizens Support Scheme on mental health-related service utilisation: evidence from a natural experiment using instrumental variable analysis.BMC public health · 2026Article
- Causal inference in real-world dementia research: a systematic review protocol.Systematic reviews · 2026Article
- Comparison of two-stage methods for count data in Mendelian randomization: a simulation study.Journal of comparative effectiveness research · 2026Article
- Estimating the causal effect of cardiometabolic conditions on socioeconomic and healthcare outcomes: a scoping review of Mendelian randomization studies.Health economics review · 2026Article
- Leveraging large-scale biobanks for therapeutic target discovery.HGG advances · 2026Article
40 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewInstrumental variable (IV) methods continue to be applied to questions ranging from genetic to social epidemiology. In the epidemiologic literature, discussion of whether the assumptions underlying IV analyses hold is often limited to only certain assumptions and even then, arguments are mostly made using subject matter knowledge. To complement subject matter knowledge, there exist a variety of falsification strategies and other tools for weighing the plausibility of the assumptions underlying IV analyses. RECENT
findingsThere are many tools that can refute the IV assumptions or help estimate the magnitude or direction of possible bias if the conditions do not hold perfectly. Many of these tools, including both recently developed strategies and strategies described decades ago, are underused or only used in specific applications of IV methods in epidemiology. SUMMARY: Although estimating causal effects with IV analyses relies on unverifiable assumptions, the assumptions can sometimes be refuted. We suggest that the epidemiologists using IV analyses employ all the falsification strategies that apply to their research question in order to avoid settings that demonstrably violate a core condition for valid inference.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.