Skip to content

How to compare instrumental variable and conventional regression analyses using negative controls and bias plots

Research output: Contribution to journalArticle

Original languageEnglish
Article numberdyx014
Number of pages11
JournalInternational Journal of Epidemiology
Early online date7 Apr 2017
DOIs
StateE-pub ahead of print - 7 Apr 2017

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: 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.

Research areas

  • instrumental variables, causal inference, pharmacoepidemiology, negative controls, electronic medical records

Documents

Documents

  • Full-text PDF (final published version)

    Rights statement: This is the final published version of the article (version of record). It first appeared online via Oxford University Press at https://academic.oup.com/ije/article-lookup/doi/10.1093/ije/dyx014#64943590. Please refer to any applicable terms of use of the publisher.

    Final published version, 704 KB, PDF-document

    License: CC BY

DOI

View research connections

Related faculties, schools or groups