The Analysis of Covariance

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


Copyright © 2012

Schuyler W. Huck
All rights reserved.

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