Sample size importantly limits the usefulness of instrumental variable methods, depending on instrument strength and level of confounding

摘要

Objectives: Instrumental variable (IV) analysis is promising for estimation of therapeutic effects from observational data as it can circumvent unmeasured confounding. However, even if IV assumptions hold, IV analyses will not necessarily provide an estimate closer to the true effect than conventional analyses as this depends on the estimates' bias and variance. We investigated how estimates from standard regression (ordinary least squares [OLS]) and IV (two-stage least squares) regression compare on mean squared error (MSE).