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Related Experiment Videos

Optimum sample size determination in stratified case-control studies with cost considerations.

J M Nam1, T R Fears

  • 1Biostatistics Branch, National Cancer Institute, Rockville, Maryland 20892.

Statistics in Medicine
|February 28, 1992
PubMed
Summary

Determining sample size for Cochran's test in stratified case-control studies is crucial. Optimal allocation strategies can significantly reduce costs when control sampling expenses vary across strata.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Statistical Methods

Background:

  • Stratified case-control studies are widely used in epidemiology.
  • Cochran's test is a common statistical method for analyzing such studies.
  • Efficient sample size determination is vital for study power and resource allocation.

Purpose of the Study:

  • To develop methods for sample size determination for Cochran's test in stratified case-control studies.
  • To optimize sample allocation under fixed costs with varying control sampling expenses.
  • To investigate sample size calculations for one-to-k matched studies.

Main Methods:

  • Asymptotic methods for sample size calculation were developed and studied.
  • Numerical methods were employed for cases where optimal and standard sample sizes lack closed-form solutions.

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  • The study considered two scenarios: sampling both cases and controls, and sampling only controls when cases are given.

    • Main Results:

    • Asymptotic methods for sample size determination were established for both scenarios.
    • Numerical methods were presented for calculating sample sizes when closed-form solutions are unavailable.
    • The cost reduction from optimum allocation over standard allocation increases with greater differences in stratum-specific control sampling costs.

    Conclusions:

    • The proposed methods provide a framework for efficient sample size determination in stratified case-control studies.
    • Optimal allocation strategies are particularly beneficial when control sampling costs differ significantly across strata.
    • Numerical approaches are essential for practical implementation when analytical solutions are not feasible.