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Related Experiment Videos

Sample sizes for repeated measurements in dichotomous data.

K J Lui1

  • 1Department of Mathematical Sciences, College of Sciences, San Diego State University 92182-0314.

Statistics in Medicine
|March 1, 1991
PubMed
Summary
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This study introduces sample size formulas for repeated dichotomous measurements. It offers a cost-effective alternative to increasing subject numbers for enhanced study power.

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Power Analysis

Background:

  • Increasing statistical power often requires larger sample sizes, which can be costly.
  • Repeated measurements within subjects can improve study efficiency when subject recruitment is expensive.

Purpose of the Study:

  • To present sample size formulas for studies involving repeated dichotomous measurements.
  • To provide guidance on optimal sample allocation for such study designs.

Main Methods:

  • Derivation of sample size formulas tailored for dichotomous outcomes with repeated measures.
  • Exploration of different scenarios for applying these formulas.
  • Discussion on optimizing the distribution of subjects across measurement points.

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Main Results:

  • Novel sample size calculation methods are presented for repeated dichotomous measurements.
  • Formulas are provided for various study situations, accounting for within-subject outcome variability.
  • Optimal allocation strategies are discussed to maximize study power or minimize costs.

Conclusions:

  • Repeated measurements offer a viable strategy to increase statistical power or reduce costs in dichotomous outcome studies.
  • The presented formulas and allocation methods provide practical tools for researchers designing such studies.