title: Issues in the reporting and conduct of instrumental variable studies: a systematic review.
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.
authors.affiliation: Medical Research Council Centre for Causal Analyses and Translational Epidemiology, School of Social and Community Medicine, Faculty of Medicine and Dentistry, University of Bristol, Barley House, Oakfield Grove, Bristol, United Kingdom. neil.davies@bristol.ac.uk
authors.forename: Neil M
authors.initials: NM
authors.lastname: Davies
authors.forename: George Davey
authors.initials: GD
authors.lastname: Smith
authors.forename: Frank
authors.initials: F
authors.lastname: Windmeijer
authors.forename: Richard M
authors.initials: RM
authors.lastname: Martin
mesh_terms: D015984:Causality; D015986:Confounding Factors, Epidemiologic; D003627:Data Interpretation, Statistical; D015340:Epidemiologic Research Design; D015233:Models, Statistical; D058028:Research Report