Detecting bias with confidence in observational studies

Abstract

SUMMARY In an observational study, detecting hidden bias involves checking that treatment effects appear where they should, and not elsewhere. For instance, treated and control groups are often compared with respect to outcomes the treatment should not affect. This paper uses such a test for bias to obtain a confidence set for an unobserved covariate. The impact of this unobserved covariate is indicated by a sensitivity analysis with the covariate confined to the confidence set. In this way, a test for bias may indicate either the presence and magnitude of a hidden bias or else a reduction in the sensitivity to bias.