title: 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 conservative using an unadjusted model. Power decreased with both increasing covariate effect on the outcome as well as the misclassification rate. Treatment effect estimates were biased towards the null for both the misclassified and unadjusted models. For the count outcome using a Poisson model, covariate misclassification led to inflated type I error probabilities and reduced power in the misclassified and the unadjusted model. The impact of covariate misclassification under covariate-adaptive randomization differs depending on the underlying distribution of the outcome.
authors.affiliation: 1 Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Liqiong
authors.initials: L
authors.lastname: Fan
authors.affiliation: 1 Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Sharon D
authors.initials: SD
authors.lastname: Yeatts
authors.affiliation: 1 Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Bethany J
authors.initials: BJ
authors.lastname: Wolf
authors.affiliation: 2 Department of Epidemiology & Biostatistics, Drexel University, Philadelphia, PA, USA.
authors.forename: Leslie A
authors.initials: LA
authors.lastname: McClure
authors.affiliation: 3 Beth Israel Deaconess Medical Center, Department of Neurology,Division of Cerebrovascular Diseases, Boston MA, USA.
authors.forename: Magdy
authors.initials: M
authors.lastname: Selim
authors.affiliation: 1 Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Yuko Y
authors.initials: YY
authors.lastname: Palesch
mesh_terms: D000465:Algorithms; D015982:Bias; D016014:Linear Models; D016012:Poisson Distribution; D011897:Random Allocation
keywords: Covariate–adaptive randomization; covariate misclassification; generalized linear regression