A Bespoke Instrumental Variable Approach to Correction for Exposure Measurement Error.

ABSTRACT: A covariate-adjusted estimate of an exposure-outcome association may be biased if the exposure variable suffers measurement error. We propose an approach to correct for exposure measurement error in a covariate-adjusted estimate of the association between a continuous exposure variable and outcome of interest. Our proposed approach requires data for a reference population in which the exposure was a priori set to some known level (e.g., 0, and is therefore unexposed); however, our approach does not require an exposure validation study or replicate measures of exposure, which are typically needed when addressing bias due to exposure measurement error. A key condition for this method, which we refer to as "partial population exchangeability," requires that the association between a measured

SUBMITTER: Richardson DB 

PROVIDER: S-EPMC10144664 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature