Statistical Models Commons^™

Multiple Imputation To Correct For Measurement Error In Admixture Estimates In Genetic Structured Association Testing, Miguel A. Padilla, Jamin Divers, Laura K. Vaughan, David B. Allison, Hemant K. Tiwari

Psychology Faculty Publications

Objectives: Structured association tests ( SAT), like any statistical model, assumes that all variables are measured without error. Measurement error can bias parameter estimates and confound residual variance in linear models. It has been shown that admixture estimates can be contaminated with measurement error causing SAT models to suffer from the same afflictions. Multiple imputation (MI) is presented as a viable tool for correcting measurement error problems in SAT linear models with emphasis on correcting measurement error contaminated admixture estimates. Methods: Several MI methods are presented and compared, via simulation, in terms of controlling Type I error rates for both …