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Sample size for case-control studies using Cochran's statistic.

R F Woolson, J A Bean, P B Rojas

    Biometrics
    |December 1, 1986
    PubMed
    Summary
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    Sample size calculations for chronic disease case-control studies should account for data stratification. Ignoring stratification can lead to inadequate sample sizes for analyses using Cochran's or Mantel-Haenszel statistics.

    Area of Science:

    • Epidemiology
    • Biostatistics

    Background:

    • Case-control studies are crucial for investigating chronic diseases.
    • Standard sample size calculations often simplify data to 2x2 tables, ignoring stratification.
    • This simplification can result in insufficient statistical power for analyses.

    Purpose of the Study:

    • To develop a sample size formula for stratified case-control studies.
    • To compare this new formula with existing methods for stratified and unstratified data.
    • To address the limitations of current sample size determination in chronic disease research.

    Main Methods:

    • Derivation of a sample size formula based on Cochran's statistic for stratified data.
    • Comparison of the derived formula with formulas for unstratified data.

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  • Comparison with other proposed formulas for stratified analysis, noting differences in margin assumptions.

    • Main Results:

    • The newly derived formula provides sample size estimates.
    • The formula yields slightly larger sample sizes compared to the Muñoz and Rosner (1984) formula.
    • The difference in results stems from varying assumptions about fixed margins in the 2x2 tables.

    Conclusions:

    • The proposed sample size formula is more appropriate for stratified case-control analyses.
    • Accurate sample size determination is essential for achieving desired statistical power.
    • Considering stratification in sample size calculations improves the reliability of chronic disease studies.