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Sample sizes for individually matched case-control studies: a group sequential approach

B S Pasternack, R E Shore

    American Journal of Epidemiology
    |May 1, 1982
    PubMed
    Summary
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    Group sequential methods offer a more efficient sample size calculation for matched case-control studies compared to traditional fixed plans. These multistage approaches maintain accurate error rates and are robust for various matching scenarios.

    Area of Science:

    • Epidemiology
    • Biostatistics

    Background:

    • Individually matched case-control studies are crucial for epidemiological research.
    • Calculating appropriate sample sizes is essential for study power and efficiency.
    • Traditional fixed sample size plans may not be optimal for all study designs.

    Purpose of the Study:

    • To propose and evaluate group sequential methods for sample size determination in individually matched case-control studies.
    • To compare the efficiency of group sequential designs against conventional fixed sample size plans.
    • To assess the performance of group sequential methods under different matching conditions and variable associations.

    Main Methods:

    • Application of group sequential methods to matched pair and multiple matched control designs.
    • Comparison of average sample sizes between group sequential and fixed sample size plans.

    Related Experiment Videos

  • Computer simulations to evaluate type I and type II error rates and statistical power.

    • Main Results:

    • Group sequential designs generally require smaller average sample sizes than fixed sample size plans.
    • Simulations confirmed that group sequential methods maintain appropriate type I and type II error rates.
    • A minimal loss of power was observed when matching variables were associated with exposure but not disease.

    Conclusions:

    • Group sequential methods provide an efficient alternative for sample size calculations in matched case-control studies.
    • These methods are effective for both one-to-one and multiple matching scenarios.
    • The efficiency gains make group sequential designs a valuable tool for epidemiological research planning.