Practical Considerations for Sandwich Variance Estimation in 2-Stage Regression Settings.

ABSTRACT: In this paper, we present a practical approach for computing the sandwich variance estimator in 2-stage regression model settings. As a motivating example for 2-stage regression, we consider regression calibration, a popular approach for addressing covariate measurement error. The sandwich variance approach has rarely been applied in regression calibration, despite its requiring less computation time than popular resampling approaches for variance estimation, specifically the bootstrap. This is probably because it requires specialized statistical coding. Here we first outline the steps needed to compute the sandwich variance estimator. We then develop a convenient method of computation in R for sandwich variance estimation, which leverages standard regression model outputs and existing R f

SUBMITTER: Boe LA 

PROVIDER: S-EPMC11484631 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature