title: How to compare instrumental variable and conventional regression analyses using negative controls and bias plots.
abstract: There is increasing interest in the use of instrumental variable analysis to overcome unmeasured confounding in observational pharmacoepidemiological studies. This is partly because instrumental variable analyses are potentially less biased than conventional regression analyses. However, instrumental variable analyses are less precise, and regulators and clinicians find it difficult to interpret conflicting evidence from instrumental variable compared with conventional regression analyses. In this paper, we describe three techniques to assess which approach (instrumental variable versus conventional regression analyses) is least biased. These techniques are negative control outcomes, negative control populations and tests of covariate balance. We illustrate these methods using an analysis of the effects of smoking cessation therapies (varenicline) prescribed in primary care.
authors.affiliation: Medical Research Council Integrative Epidemiology Unit.|School of Social and Community Medicine.
authors.forename: Neil M
authors.initials: NM
authors.lastname: Davies
authors.affiliation: Medical Research Council Integrative Epidemiology Unit.
authors.forename: Kyla H
authors.initials: KH
authors.lastname: Thomas
authors.affiliation: Medical Research Council Integrative Epidemiology Unit.|UK Centre for Tobacco and Alcohol Studies.
authors.forename: Amy E
authors.initials: AE
authors.lastname: Taylor
authors.affiliation: Medical Research Council Integrative Epidemiology Unit.|School of Social and Community Medicine.|UK Centre for Tobacco and Alcohol Studies.
authors.forename: Gemma M J
authors.initials: GMJ
authors.lastname: Taylor
authors.affiliation: Medical Research Council Integrative Epidemiology Unit.|School of Social and Community Medicine.
authors.forename: Richard M
authors.initials: RM
authors.lastname: Martin
authors.affiliation: Medical Research Council Integrative Epidemiology Unit.|UK Centre for Tobacco and Alcohol Studies.
authors.forename: Marcus R
authors.initials: MR
authors.lastname: Munafò
authors.affiliation: Medical Research Council Integrative Epidemiology Unit.|Department of Economics, University of Bristol, Bristol, UK.
authors.forename: Frank
authors.initials: F
authors.lastname: Windmeijer
mesh_terms: D015982:Bias; D016022:Case-Control Studies; D015984:Causality; D015986:Confounding Factors, Epidemiologic; D003627:Data Interpretation, Statistical; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D017891:Pharmacoepidemiology; D012044:Regression Analysis
keywords: Instrumental variables; causal inference; negative controls; pharmacoepidemiology