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

Int J Epidemiol 2017 12;46(6):2067-2077

Medical Research Council Integrative Epidemiology Unit.

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.

Download full-text PDF

Source
http://dx.doi.org/10.1093/ije/dyx014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837536PMC
December 2017
12 Reads

Publication Analysis

Top Keywords

instrumental variable
24
regression analyses
16
conventional regression
16
negative control
8
analyses biased
8
variable analyses
8
variable
6
analyses
6
instrumental
5
difficult interpret
4
illustrate methods
4
interpret conflicting
4
evidence instrumental
4
conflicting evidence
4
find difficult
4
balance illustrate
4
analysis effects
4
analyses precise
4
effects smoking
4
analyses instrumental
4

Similar Publications