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[Recent methodological advances in measuring mortality differentials].

R Hakkert

    Revista Brasileira De Estudos De Populacao
    |January 1, 1984
    PubMed
    Summary
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    This study introduces regression models for analyzing differential mortality across multiple factors, especially with small sample sizes. It explains Cox

    Area of Science:

    • Biostatistics
    • Demography
    • Epidemiology

    Background:

    • Analyzing differential mortality with multiple criteria is challenging due to small sample sizes limiting cross-tabulation.
    • Regression models offer advanced techniques to overcome these limitations in mortality analysis.

    Purpose of the Study:

    • To introduce nonspecialists to regression techniques for differential mortality analysis.
    • To explain the logic, advantages, and disadvantages of Cox's proportional hazards method.
    • To suggest alternatives and discuss extensions for human population mortality studies.

    Main Methods:

    • Discussion of recent regression-based techniques for multivariate mortality analysis.
    • Detailed explanation of Cox's proportional hazards model.
    Keywords:
    BibliographyData AnalysisDemographic AnalysisDemographic FactorsDifferential MortalityEstimation TechnicsEvaluationMathematical ModelMethodological StudiesModels, TheoreticalMortalityPopulationPopulation DynamicsResearch Methodology

    Related Experiment Videos

  • Exploration of alternatives and extensions like indirect estimation.

    • Main Results:

    • Regression models facilitate differential mortality analysis with simultaneous criteria, even with small samples.
    • Cox's proportional hazards model is a common but not always optimal approach.
    • Alternative methods and strategies for handling unexplained heterogeneity are presented.

    Conclusions:

    • Regression techniques, particularly Cox's model and its alternatives, are essential for complex mortality studies.
    • Understanding these methods aids in more accurate human population mortality analysis.
    • Further research can extend these methods to indirect estimation and unexplained heterogeneity.