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Related Experiment Videos

Sample size determination for multiple comparison studies treating confidence interval width as random.

Z Pan1, L L Kupper

  • 1Division of Biostatistics, Family Health International, P.O. Box 13950, Research Triangle Park, NC 27709, USA.

Statistics in Medicine
|July 9, 1999
PubMed
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Determining optimal sample size for multiple comparisons requires accounting for the random nature of pooled sample variance. This approach ensures confidence intervals are both accurate and sufficiently narrow, unlike traditional methods.

Area of Science:

  • Statistics
  • Biostatistics
  • Experimental Design

Background:

  • Accurate sample size determination is crucial for reliable statistical inferences.
  • Traditional methods often overlook the variability of the pooled sample variance.
  • This can lead to underestimation of required sample sizes and reduced statistical power.

Purpose of the Study:

  • To develop methods for optimal sample size determination in multiple comparison procedures.
  • To account for the stochastic nature of the pooled sample variance in sample size calculations.
  • To ensure simultaneous coverage and desired width for multiple confidence intervals.

Main Methods:

  • Utilized four popular multiple comparison procedures: Scheffe's, Bonferroni's, Tukey's, and Dunnett's.

Related Experiment Videos

  • Defined optimal sample size (n*m) to achieve a specified coverage probability (1-alpha) and tolerance probability (1-gamma).
  • Incorporated the pooled sample variance (S2p) as a random variable in the calculations.

    • Main Results:

    • Compared a novel approach to traditional methods that ignore the random nature of S2p.
    • Demonstrated that traditional methods can lead to significant underestimation of sample size.
    • The proposed approach guarantees a lower bound of [1-(alpha+gamma)] for simultaneous coverage and interval width.

    Conclusions:

    • The developed methods provide a more robust approach to sample size determination for multiple comparisons.
    • Accounting for the pooled sample variance variability is essential for accurate sample size estimation.
    • Recommendations are offered for selecting appropriate multiple comparison procedures for inference and sample size planning.