The impact of covariate misclassification using generalized linear regression under covariate-adaptive randomization.

ABSTRACT: Under covariate adaptive randomization, the covariate is tied to both randomization and analysis. Misclassification of such covariate will impact the intended treatment assignment; further, it is unclear what the appropriate analysis strategy should be. We explore the impact of such misclassification on the trial's statistical operating characteristics. Simulation scenarios were created based on the misclassification rate and the covariate effect on the outcome. Models including unadjusted, adjusted for the misclassified, or adjusted for the corrected covariate were compared using logistic regression for a binary outcome and Poisson regression for a count outcome. For the binary outcome using logistic regression, type I error can be maintained in the adjusted model, but the test is conserv

SUBMITTER: Fan L 

PROVIDER: S-EPMC5476516 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature