Using the analysis of covariance to increase the power of priming experiments.

Although priming paradigms are widely used in cognitive psychology, the statistical analyses typically applied to priming data may not be optimal. Conceiving of priming paradigms as change-from-baseline designs suggests that the analysis of covariance (ANCOVA), using baseline performance as the covariate, is a more efficient (i.e., powerful) analysis. Specifically, ANCOVA provides more powerful tests of 1) the presence of priming and 2) between-group differences in priming. In addition, for within-subject designs with multiple baseline conditions, ANCOVA may increase the power of within-subjects effects. Efficiency gains are demonstrated with a re-analysis of priming datasets from implicit memory research. It is suggested that similar gains may be realized in other areas of priming research. Important assumptions of this procedure, which must be evaluated for the appropriate application of ANCOVA, are discussed.