2. Review of Simple Correlated Samples Designs and Associated Analyses

  1. Bradley E. Huitema

Published Online: 14 OCT 2011

DOI: 10.1002/9781118067475.ch2

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) Review of Simple Correlated Samples Designs and Associated Analyses, 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.ch2

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:

  • correlated associated analyses;
  • matched pairs experiment;
  • pretest–posttest study;
  • software;
  • two-level correlated samples designs;
  • two-level repeated measures experiment

Summary

This chapter reviews three simple correlated samples designs that are common in behavioral and biomedical science research. The conventional analyses for these designs are also reviewed. The most typical randomized groups experiments and observational studies are based on two independent samples, but it is not unusual to encounter designs that yield correlated samples. The three most popular designs that yield correlated (or dependent) samples are the pretest–posttest study, the matched pairs experiment, and the two-level repeated measures experiment. The most common parametric method of analysis for the three correlated samples designs described is the correlated samples t-test. The major advantage of correlated samples designs is that the dependency among the observations leads to analyses having higher power than is obtained using conventional independent samples approaches.

Controlled Vocabulary Terms

correlation; measures of dispersion; statistical software