25. Randomized Pretest–Posttest Designs

  1. Bradley E. Huitema

Published Online: 14 OCT 2011

DOI: 10.1002/9781118067475.ch25

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) Randomized Pretest–Posttest Designs, 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.ch25

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:

  • ANCOVA;
  • ANOVA methods;
  • pretest-posttest designs

Summary

Pretest–posttest designs designs are analyzed using one-factor ANOVA on the posttest. This chapter points out relationships among these methods, to explain why the two-factor ANOVA approach is often misleading, and to explain why ANCOVA is usually better than all the ANOVA alternatives. In the chapter the covariate is an early measurement on the variable to be used as the dependent variable rather than a separate variable measured in a different way. The analysis is carried out by using the pretest as the covariate and the posttest as the dependent variable. Frequently encountered analytic procedures include (1) one factor ANOVA on the posttest, (2) one-factor ANOVA on difference scores, and (3) two-factor ANOVA. These methods are less satisfactory than ANCOVA because they do not adjust for chance differences on the pretest and they generally have lower power.

Controlled Vocabulary Terms

analysis of covariance; analysis of variance