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Power and sample size calculations for exact conditional tests with ordered categorical data

J F Hilton1, C R Mehta

  • 1Department of Epidemiology and Biostatistics, University of California, San Francisco 94143-0560.

Biometrics
|June 1, 1993
PubMed
Summary
This summary is machine-generated.

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This study introduces a new algorithm for calculating sample sizes for categorical data, applicable to various rank statistics. It offers accurate sample size determination using exact power or Monte Carlo estimates, improving statistical analysis efficiency.

Area of Science:

  • Statistics
  • Biostatistics
  • Data Analysis

Background:

  • Determining appropriate sample sizes is crucial for the statistical power of studies involving categorical data.
  • Existing methods may lack flexibility or computational efficiency for complex rank statistics.

Purpose of the Study:

  • To develop a versatile algorithm for computing sample sizes for categorical data.
  • To accommodate both equal and unequal sample sizes across different statistical tests.

Main Methods:

  • An algorithm was developed for sample size computation in categorical data settings.
  • The algorithm supports linear rank statistics, including the Wilcoxon rank-sum statistic, and can be extended to nonlinear statistics.
  • Sample size determination can utilize exact power calculations or precise Monte Carlo estimates.

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Main Results:

  • The algorithm efficiently computes sample sizes for various rank statistics.
  • Power can be approximated using asymptotic critical values for a reduced computational load when the number of categories is sufficient (e.g., >5 for Wilcoxon).
  • The method provides accurate sample size recommendations for studies with categorical outcomes.

Conclusions:

  • The developed algorithm offers a flexible and efficient approach to sample size calculation for categorical data.
  • It enhances the rigor of statistical planning in research involving rank-based tests.
  • The findings support improved study design and power analysis in various scientific fields.