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 one-way ANCOVA
- Results of four separate two-way 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
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