Using group mean centering for computing adjusted means by site in a randomized experimental design: The case of California's work pays demonstration project

When analyzing data from a randomized experiment that is replicated across multiple sites and includes covariates, the covariates can adjust for differences from either the grand mean or the group (site) mean. The analysis strategy determines the reference point. Pooling the sites and using a standard analysis of covariance (ANCOVA) adjusts for differences around the grand mean, whereas analyzing each site separately adjusts for differences around each group (site) mean. This article demonstrates that group mean centering permits pooling data from multiple sites into a single analysis while still using the group mean as a reference point for evaluating the covariate.