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Related Experiment Videos

Global tests for multiple binary outcomes

M Lefkopoulou1, L Ryan

  • 1Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.

Biometrics
|December 1, 1993
PubMed
Summary
This summary is machine-generated.

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This study introduces new statistical tests for comparing multiple binary outcomes, especially for clustered data. A simplified approach of collapsing data can be surprisingly efficient for rare outcomes.

Area of Science:

  • Statistics
  • Biostatistics
  • Quantitative Methods

Background:

  • Applied statisticians frequently need to compare multiple groups across several outcomes.
  • Existing methods include data summarization, multiple comparison adjustments, and global multivariate tests.
  • Global tests are more sensitive for normal data, but their properties for multiple binary outcomes, especially with clustered data, are less understood.

Purpose of the Study:

  • To derive and evaluate quasi-likelihood score tests for multiple binary outcomes.
  • To extend these tests for clustered data and compare them with existing methods.
  • To assess the efficiency of a collapsed data approach versus multivariate models.

Main Methods:

  • Derivation of a class of quasi-likelihood score tests for multiple binary outcomes.

Related Experiment Videos

  • Development of extensions for clustered data.
  • Asymptotic relative efficiency analysis comparing different testing strategies.

    • Main Results:

    • Special cases of the derived tests correspond to previously proposed methods.
    • The efficiency of tests depends on outcome correlation and response probabilities.
    • A collapsed data approach demonstrates high efficiency for rare outcomes.

    Conclusions:

    • Quasi-likelihood score tests offer a flexible framework for analyzing multiple binary outcomes.
    • While global multivariate tests are generally recommended, the collapsed data method is a viable and efficient alternative for rare outcomes.
    • Findings are illustrated using developmental toxicity study data.