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Inference for odds ratio regression models with sparse dependent data

J J Hanfelt1, K Y Liang

  • 1Department of Biomathematics and Biostatistics, Georgetown University, Washington, D.C. 20007, USA. hanfelt@gunet.georgetown.edu

Biometrics
|April 17, 1998
PubMed
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This study introduces a new Mantel-Haenszel quasi-likelihood method for analyzing dependent data in case-control studies. This approach improves statistical inference, particularly for additive regression models, offering a robust alternative to existing methods.

Area of Science:

  • Biostatistics
  • Epidemiology
  • Statistical Genetics

Background:

  • Analyzing dependent data in case-control studies, common in family-based or longitudinal designs, presents statistical challenges.
  • Traditional methods like noncentral hypergeometric likelihood can be sensitive to unknown dependence structures.

Purpose of the Study:

  • To develop robust statistical inference methods for regression models of odds ratios with table-level covariates when within-table observations are dependent.
  • To address limitations of existing methods, specifically the poor performance of Wald confidence intervals in additive regression models.

Main Methods:

  • Utilized estimating functions based on the Mantel-Haenszel method for consistent estimation of regression parameters (beta).
  • Proposed and evaluated a novel Mantel-Haenszel quasi-likelihood function derived from integrating the Mantel-Haenszel estimating function.

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  • Conducted a simulation study to compare the performance of the proposed method against Wald inference and other approaches.

    • Main Results:

    • The Mantel-Haenszel estimating function approach provides consistent estimators for beta.
    • Wald's confidence intervals show good performance for multiplicative regression but poor coverage for additive models.
    • The proposed Mantel-Haenszel quasi-likelihood method demonstrated superior inference in additive models and comparable performance to Wald's method in multiplicative models, especially in medium-sized samples.

    Conclusions:

    • The Mantel-Haenszel quasi-likelihood approach offers a reliable method for statistical inference in regression models with dependent data, particularly under additive models.
    • This method provides a valuable tool for analyzing complex epidemiological data, such as familial risk studies, where dependence structures are prevalent.