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Related Experiment Videos

Sample size tables for logistic regression.

F Y Hsieh1

  • 1Department of Epidemiology and Social Medicine, Albert Einstein College of Medicine, Bronx, NY 10461.

Statistics in Medicine
|July 1, 1989
PubMed
Summary
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This study provides new sample size tables for logistic regression in epidemiology. These tables are accurate for most common risk factor distributions and varying event proportions, aiding study power calculations.

Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Determining appropriate sample size is crucial for the statistical power and validity of epidemiologic studies.
  • Existing methods for sample size calculation may have limitations in various logistic regression scenarios.

Purpose of the Study:

  • To present extended sample size tables for logistic regression analyses in epidemiologic research.
  • To evaluate the accuracy and applicability of these tables across different study conditions.

Main Methods:

  • Utilized Whittemore's formula to extend existing sample size calculation methods.
  • Employed Monte Carlo simulations to assess table performance under various conditions.

Main Results:

  • The developed sample size tables are suitable for studies with both high and low event proportions.

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  • Tables demonstrate reasonable accuracy for normal and exponential risk factor distributions, with limitations for double exponential distributions.
  • Study power is influenced by the number of events and the number of individuals at risk.

    • Conclusions:

    • The presented sample size tables offer a practical tool for epidemiologic studies using logistic regression.
    • Researchers can confidently use these tables for planning studies with common risk factor distributions and varying event rates.
    • Understanding the interplay between sample size, events, and power is essential for robust study design.