6. One-Factor Analysis of Covariance

  1. Bradley E. Huitema

Published Online: 14 OCT 2011

DOI: 10.1002/9781118067475.ch6

The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition

The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition

How to Cite

Huitema, B. E. (2011) One-Factor Analysis of Covariance, in The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118067475.ch6

Author Information

  1. Department of Psychology, Western Michigan University, Kalamazoo, Michigan, USA

Publication History

  1. Published Online: 14 OCT 2011
  2. Published Print: 14 OCT 2011

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780471748960

Online ISBN: 9781118067475

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Keywords:

  • adjusted mean;
  • analysis of covariance (ANCOVA);
  • analysis of variance (ANOVA);
  • covariance model

Summary

Similar to the analysis of variance, the analysis of covariance (ANCOVA) is used to test the null hypothesis that two or more population means are equal. Although the traditional approach to conceptualizing the ANCOVA is to view it as an integration of ANOVA and ANOVAR, an alternative approach is to view it as a minor variant of multiple regression analysis. As each approach has advantages both of them are presented. Performance on a response variable is conceptualized in three different ways under the ANOVA, ANOVAR, and ANCOVA models. The interpretation of ANCOVA and the associated adjusted means relies very heavily on the assumption of homogeneous regression slopes for the various treatment groups.

Controlled Vocabulary Terms

Adjusted mean; analysis of covariance; analysis of variance; computational statistics