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Data analytic methods for matched case-control studies.

D Pregibon

    Biometrics
    |September 1, 1984
    PubMed
    Summary

    Complex statistical models in matched case-control studies offer insights but can hide data patterns. Proper diagnostic methods are crucial for reliable disease risk analysis.

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    Resistant fits for some commonly used logistic models with medical application.

    Biometrics·1982

    Area of Science:

    • Biostatistics
    • Epidemiology
    • Statistical Modeling

    Background:

    • Multivariate statistical models enhance understanding of disease risk factors in matched case-control studies.
    • However, complex models may obscure important data features, necessitating robust analytical support.
    • Current methods often lack sufficient diagnostic tools for routine application.

    Purpose of the Study:

    • To explore the application of logistic models in matched case-control studies.
    • To emphasize analogies between logistic and linear regression models.
    • To introduce regression diagnostics for evaluating model fit and reliability.

    Main Methods:

    • Analysis of matched case-control data using logistic regression.
    • Application of concepts analogous to linear regression, including analysis of variance and correlation.
    • Introduction and illustration of regression diagnostic techniques.
    • Case study: bladder cancer in males.

    Main Results:

    • Demonstration of how logistic models can be analyzed using familiar statistical concepts.
    • Illustration of regression diagnostics for assessing goodness of fit.
    • Highlighting the importance of examining model fit beyond standard error calculations.

    Conclusions:

    • Effective use of complex statistical models in matched case-control studies requires comprehensive diagnostic evaluation.
    • Regression diagnostics are essential for trusting inferences drawn from these models.
    • The presented methods, illustrated with a bladder cancer study, aid in robust disease risk analysis.

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