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Sample sizes for constructing confidence intervals and testing hypotheses.

D R Bristol1

  • 1Development Department, CIBA-GEIGY Corporation, Summit, NJ 07901.

Statistics in Medicine
|July 1, 1989
PubMed
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Sample size determination for clinical trials can align with confidence interval analysis. This study compares methods for sample size calculation using confidence interval length versus traditional power control.

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Inference

Background:

  • Hypothesis testing and p-values are traditional methods for clinical trial analysis.
  • Estimation and confidence intervals are increasingly favored for statistical inference.
  • Sample size determination often relies on power control, even when confidence intervals are used for analysis.

Purpose of the Study:

  • To compare sample size determination methods for randomized clinical trials.
  • To evaluate the consistency between data analysis techniques and sample size calculation.
  • To contrast sample size determination based on confidence interval length with power control.

Main Methods:

  • The study involves a comparative analysis of two sample size determination approaches.

Related Experiment Videos

  • Method 1: Sample size calculation based on controlling the length of the confidence interval.
  • Method 2: Sample size calculation based on controlling the power of a statistical test.

    • Main Results:

    • The paper presents a comparison of sample size requirements under both methods.
    • Results indicate potential differences in sample sizes obtained by the two approaches.
    • The findings highlight the implications for achieving consistency in trial design.

    Conclusions:

    • Aligning sample size determination with confidence interval-based analysis is feasible.
    • Using confidence interval length for sample size calculation offers an alternative to power control.
    • Consistency between inference and sample size methods can enhance clinical trial design.