Literature DB >> 23532055

Issues in the reporting and conduct of instrumental variable studies: a systematic review.

Neil M Davies1, George Davey Smith, Frank Windmeijer, Richard M Martin.   

Abstract

Instrumental variables can be used to estimate the causal effects of exposures on outcomes in the presence of residual or uncontrolled confounding. To assess the validity of analyses using instrumental variables, specific information about whether underlying assumptions are met must be presented, in particular to demonstrate that the instrument is associated with the exposure but not with measured confounding factors. We systematically reviewed the epidemiological literature in Embase and Medline for articles containing the term "instrumental variable$" to investigate whether reporting of test statistics in studies using instrumental variables was sufficient to assess the validity of the results. We extracted the information each study reported about their instrumental variables, including specification tests used to check assumptions. The search found 756 studies of which 90 were relevant and were included. Only 25 (28%) studies reported appropriate tests of the strength of the associations between instruments and exposure. Forty-four (49%) studies reported associations between the instrumental variables and observed covariates. Studies using instrumental variables had wide confidence intervals and so effect estimates were imprecise. We propose a checklist of information and specification tests that studies using instrumental variables should report.

Mesh:

Year:  2013        PMID: 23532055     DOI: 10.1097/EDE.0b013e31828abafb

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  49 in total

1.  Methodological considerations in assessing the effectiveness of antidepressant medication continuation during pregnancy using administrative data.

Authors:  Sonja A Swanson; Sonia Hernandez-Diaz; Kristin Palmsten; Helen Mogun; Mark Olfson; Krista F Huybrechts
Journal:  Pharmacoepidemiol Drug Saf       Date:  2015-06-04       Impact factor: 2.890

2.  Varenicline versus nicotine replacement therapy for long-term smoking cessation: an observational study using the Clinical Practice Research Datalink.

Authors:  Neil M Davies; Amy E Taylor; Gemma Mj Taylor; Taha Itani; Tim Jones; Richard M Martin; Marcus R Munafò; Frank Windmeijer; Kyla H Thomas
Journal:  Health Technol Assess       Date:  2020-02       Impact factor: 4.014

3.  Selecting on treatment: a pervasive form of bias in instrumental variable analyses.

Authors:  Sonja A Swanson; James M Robins; Matthew Miller; Miguel A Hernán
Journal:  Am J Epidemiol       Date:  2015-01-21       Impact factor: 4.897

4.  The challenging interpretation of instrumental variable estimates under monotonicity.

Authors:  Sonja A Swanson; Miguel A Hernán
Journal:  Int J Epidemiol       Date:  2018-08-01       Impact factor: 7.196

5.  Toward a clearer portrayal of confounding bias in instrumental variable applications.

Authors:  John W Jackson; Sonja A Swanson
Journal:  Epidemiology       Date:  2015-07       Impact factor: 4.822

6.  A network's gender composition and communication pattern predict women's leadership success.

Authors:  Yang Yang; Nitesh V Chawla; Brian Uzzi
Journal:  Proc Natl Acad Sci U S A       Date:  2019-01-22       Impact factor: 11.205

Review 7.  Methods to control for unmeasured confounding in pharmacoepidemiology: an overview.

Authors:  Md Jamal Uddin; Rolf H H Groenwold; Mohammed Sanni Ali; Anthonius de Boer; Kit C B Roes; Muhammad A B Chowdhury; Olaf H Klungel
Journal:  Int J Clin Pharm       Date:  2016-04-18

Review 8.  Mendelian Randomization as an Approach to Assess Causality Using Observational Data.

Authors:  Peggy Sekula; Fabiola Del Greco M; Cristian Pattaro; Anna Köttgen
Journal:  J Am Soc Nephrol       Date:  2016-08-02       Impact factor: 10.121

9.  Definition and evaluation of the monotonicity condition for preference-based instruments.

Authors:  Sonja A Swanson; Matthew Miller; James M Robins; Miguel A Hernán
Journal:  Epidemiology       Date:  2015-05       Impact factor: 4.822

10.  Instrumental variable analysis of multiplicative models with potentially invalid instruments.

Authors:  Michelle Shardell; Luigi Ferrucci
Journal:  Stat Med       Date:  2016-08-16       Impact factor: 2.373

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