Sensitivity analysis for random measurement error using regression calibration and simulation-extrapolation.

ABSTRACT:

Objective

Sensitivity analysis for random measurement error can be applied in the absence of validation data by means of regression calibration and simulation-extrapolation. These have not been compared for this purpose.

Study design and setting

A simulation study was conducted comparing the performance of regression calibration and simulation-extrapolation for linear and logistic regression. The performance of the two methods was evaluated in terms of bias, mean squared error (MSE) and confidence interval coverage, for various values of reliability of the error-prone measurement (0.05-0.91), sample size (125-4000), number of replicates (2-10), and R-squared (0.03-0.75). It was assumed that no validation data were available about the error-free measures, while correct inform

SUBMITTER: Nab L 

PROVIDER: S-EPMC10446124 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature