ArticleAnnals of translational medicine2018
Instrumental variable analysis in the presence of unmeasured confounding.
Article in Annals of translational medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
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.
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Who cites it
14 citing papers in PubMed.
- Understanding the Comorbidities Among Psychiatric Disorders, Chronic Low Back Pain, and Spinal Degenerative Disease Using Observational and Genetically Informed Analyses.Biological psychiatry global open science · 2025Article
- The effect of indoor air pollution on under-five child health in South Sudan.BMC public health · 2025Article
- Assessing the performance of physician's prescribing preference as an instrumental variable in comparative effectiveness research with moderate and small sample sizes: a simulation study.Journal of comparative effectiveness research · 2024Article
- Instrumental Variable Analysis of Racial Discrimination and Blood Pressure in a Sample of Young Adults.American journal of epidemiology · 2023Article
- Dealing with confounding in observational studies: A scoping review of methods evaluated in simulation studies with single-point exposure.Statistics in medicine · 2023Article
- Epidemiologic and Genetic Associations of Endometriosis With Depression, Anxiety, and Eating Disorders.JAMA network open · 2023Article
- SNPs in lncRNA KCNQ1OT1 Modulate Its Expression and Confer Susceptibility to Salt Sensitivity of Blood Pressure in a Chinese Han Population.Nutrients · 2022Article
- Toward a better understanding about real-world evidence.European journal of hospital pharmacy : science and practice · 2022Review
- Regression discontinuity analysis for pharmacovigilance: statin example reflected trial findings showing little evidence of harm.Journal of clinical epidemiology · 2022Article
- Population-Level Analyses of Alcohol Consumption as a Predictor of Acute Atrial Fibrillation Episodes.Nature cardiovascular research · 2022Article
- Analytical methods to assess the impacts of activity-based funding (ABF): a scoping review.Health economics review · 2021Article
- Long-term use of hydrocodone vs. oxycodone in primary care.Drug and alcohol dependence · 2019Article
- Statistics in Brief: Instrumental Variable Analysis: An Underutilized Method in Orthopaedic Research.Clinical orthopaedics and related research · 2019Article
- Using Mendelian randomisation to assess causality in observational studies.Evidence-based mental health · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Observational studies are prone to bias due to confounding either measured or unmeasured. While measured confounding can be controlled for with a variety of sophisticated methods such as propensity score-based matching, stratification and multivariable regression model, the unmeasured confounding is usually cumbersome, leading to biased estimates. In econometrics, instrumental variable (IV) is widely used to control for unmeasured confounding. However, its use in clinical researches is generally less employed. In some subspecialties of clinical medicine such as pharmacoepidemiological research, IV analysis is increasingly used in recent years. With the development of electronic healthcare records, more and more healthcare data are available to clinical investigators. Such kind of data are observational in nature, thus estimates based on these data are subject to confounding. This article aims to review several methods for implementing IV analysis for binary and continuous outcomes. R code for these analyses are provided and explained in the main text.
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