Are your covariates under control? How normalization can re-introduce covariate effects.

ABSTRACT: Many statistical tests rely on the assumption that the residuals of a model are normally distributed. Rank-based inverse normal transformation (INT) of the dependent variable is one of the most popular approaches to satisfy the normality assumption. When covariates are included in the analysis, a common approach is to first adjust for the covariates and then normalize the residuals. This study investigated the effect of regressing covariates against the dependent variable and then applying rank-based INT to the residuals. The correlation between the dependent variable and covariates at each stage of processing was assessed. An alternative approach was tested in which rank-based INT was applied to the dependent variable before regressing covariates. Analyses based on both simulated and real

SUBMITTER: Pain O 

PROVIDER: S-EPMC6057994 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature