OUTLINE FOR CHAPTER
15
The Analysis of Covariance
 Introduction
 ANCOVA as an option to any analysis of variance
 The versatility of the analysis of covariance
 The Three Different Variables Involved in Any ANCOVA
Study
 The independent and dependent variables
 The covariate variable
 The Covariate's Role
 Power
 Control
 Null Hypotheses
 The number of null hypotheses in any ANCOVA study
 The meaning of the ms in any null hypothesis
 The Focus, Number, and Quality of the Covariate Variable(s)
 Using covariates that are the same or different from the dependent
variable
 Using one or multiple covariates in the same study
 The two characteristics of any good covariate
 Presentation of Results
 Results of a oneway ANCOVA
 Results of four separate twoway ANCOVAs
 Results of a mixed ANCOVA
 The Statistical Basis for ANCOVA's Power Advantage
and Adjustment Feature
 The correlation between the covariate and dependent variables
 Which correlation matters
 The correlational criterion for a "good" covariate
 Assumptions
 The independent variable should not affect the covariate variable
 Homogeneity of regression slopes
 Linearity
 Other "standard" assumptions
 ANCOVA When Comparison Groups Are Not Formed Randomly
 The meaning of intact groups
 Why ANCOVA cannot fully "equate" intact groups
 Related Issues
 Bonferroni
 Statistical significance vs. practical significance
 Planned comparisons
 Warnings
 The statistical focus: Adjusted means
 The importance of underlying assumptions
 ANCOVA vs. ANOVA
