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Mantel-Haenszel test statistics for correlated binary data

J Zhang1, D D Boos

  • 1Department of Statistics, North Carolina State University, Raleigh 27695-8203, USA.

Biometrics
|January 10, 1998
PubMed
Summary
This summary is machine-generated.

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This study introduces two new Mantel-Haenszel test statistics for correlated binary data. These new methods perform well, especially with small to moderate numbers of strata, offering improved analysis for correlated binary data.

Area of Science:

  • Biostatistics
  • Statistical Methods
  • Epidemiology

Background:

  • Correlated binary data analysis is crucial in various fields.
  • Existing Mantel-Haenszel methods have limitations with certain data structures.
  • Accurate statistical tests are needed for reliable inference.

Purpose of the Study:

  • To propose novel Mantel-Haenszel test statistics for correlated binary data.
  • To evaluate the performance of these new statistics under different limiting models.
  • To provide accurate confidence intervals for correlated binary data.

Main Methods:

  • Development of two new Mantel-Haenszel test statistics.
  • Asymptotic validity assessment in sparse data and large-strata models.
  • Monte Carlo simulations to compare performance against existing methods.

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  • Derivation and comparison of confidence intervals.

    • Main Results:

    • The proposed statistics demonstrate asymptotic validity in both sparse and large-strata limiting models.
    • Monte Carlo experiments indicate favorable comparisons with existing test statistics.
    • The new statistics show particular advantages for 5-25 small to moderate-sized strata.
    • Confidence intervals derived from the new statistics are also presented.

    Conclusions:

    • The new Mantel-Haenszel test statistics offer a robust approach for analyzing correlated binary data.
    • These statistics are particularly beneficial for studies with a limited number of strata.
    • The findings contribute to improved statistical inference in biostatistics and epidemiology.