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Epidemiologic programs for computers and calculators. Inferences on odds ratios, relative risks, and risk differences

S Wallenstein, C Bodian

    American Journal of Epidemiology
    |August 1, 1987
    PubMed
    Summary

    This study presents a method for analyzing dichotomous outcomes using generalized linear models. It enables the use of relative risks, risk differences, and odds ratios in standard statistical software.

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    Area of Science:

    • Biostatistics
    • Epidemiology
    • Statistical Modeling

    Background:

    • Statistical models analyze covariate effects on dichotomous outcomes like disease or death.
    • Common outcome functions include odds ratio, relative risk, and risk difference.
    • These models are often restricted to specialized software, limiting accessibility.

    Purpose of the Study:

    • To describe implementing maximum likelihood estimation and hypothesis testing for generalized linear models.
    • To enable the use of these models in standard statistical packages capable of weighted least squares analysis.
    • To specifically address models for relative risks, risk differences, and odds ratios.

    Main Methods:

    • Utilizing weighted least squares (WLS) analysis available in standard statistical software.

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  • Implementing maximum likelihood estimation (MLE) procedures.
  • Applying hypothesis testing techniques within the generalized linear model framework.

    • Main Results:

    • Demonstrates that generalized linear models for relative risks, risk differences, and odds ratios can be implemented using WLS.
    • Provides practical examples using SAS and SPSSx.
    • Makes advanced statistical techniques more accessible to a wider research community.

    Conclusions:

    • The described WLS approach facilitates the application of generalized linear models for common risk measures.
    • Researchers can now perform these analyses using widely available statistical software.
    • This enhances the statistical analysis capabilities for epidemiological and biostatistical research.