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Sample sizes for experiments with multivariate repeated measures

X Guo1, W D Johnson

  • 1Department of Biometry and Genetics, Louisiana State University Medical Center, New Orleans 70112-1393, USA.

Journal of Biopharmaceutical Statistics
|May 1, 1996
PubMed
Summary
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Determining sample size for multivariate repeated measures experiments is crucial. This study provides methods based on power analysis for one or two groups, aiding researchers in planning robust study designs.

Area of Science:

  • Statistics
  • Experimental Design
  • Multivariate Analysis

Background:

  • Multivariate repeated measures experiments involve complex data structures.
  • Accurate sample size determination is essential for statistical power and reliable results.
  • Existing methods may not fully address the nuances of multivariate repeated measures designs.

Purpose of the Study:

  • To discuss procedures for determining sample size in multivariate repeated measures experiments.
  • To focus on designs involving one or two independent groups.
  • To provide a basis for minimum sample size determination using power considerations.

Main Methods:

  • The study discusses power considerations for Hotelling's T2 and the F-test.
  • Procedures are presented for sample size determination with an arbitrary covariance matrix.

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  • The special case of a multivariate spherical covariance matrix is also examined.

    • Main Results:

    • The research outlines sample size determination procedures for specific experimental designs.
    • It considers power calculations for multivariate tests.
    • Tables of minimum required sample sizes for various multivariate hypotheses are presented.

    Conclusions:

    • The study offers practical guidance on sample size calculations for multivariate repeated measures.
    • It emphasizes the importance of power considerations in experimental design.
    • The provided tables serve as a valuable resource for researchers in planning their studies.