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A Real-world What-Where-When Memory Test
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Published on: May 16, 2017

[Case-control studies with multinomial responses: a proposal for analysis].

Ana Carolina Cintra Nunes Mafra1, Luciana Bertoldi Nucci, Ricardo Cordeiro

  • 1Universidade Estadual de Campinas, Campinas, Brasil. anacarol.nunes@gmail.com

Cadernos De Saude Publica
|May 14, 2010
PubMed
Summary
This summary is machine-generated.

This study highlights the polytomous logistic model as the best approach for analyzing case-control studies with multiple case types. This method enhances the identification of specific risk and protective factors for each case subclass.

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Last Updated: Jun 13, 2026

A Real-world What-Where-When Memory Test
09:13

A Real-world What-Where-When Memory Test

Published on: May 16, 2017

Area of Science:

  • Epidemiology
  • Biostatistics

Context:

  • Case-control studies are fundamental in epidemiology for investigating disease etiology.
  • Classifying cases into multiple subtypes presents analytical challenges for traditional models.

Purpose:

  • To review and discuss the application of multinomial models in case-control studies.
  • To advocate for the polytomous logistic model as the most suitable multinomial adjustment for epidemiological research.

Summary:

  • This review examines the use of multinomial models in case-control studies with multiple case classifications.
  • The polytomous logistic model is identified as the preferred method for calculating epidemiological measures of risk and association.
  • An illustrative application compares the polytomous logistic model with the binomial logistic model in a population-based study.

Impact:

  • The polytomous logistic model enables simultaneous investigation of associations between covariates and multiple case subclasses.
  • This approach facilitates the identification of individualized risk and protective factors for each specific case type.
  • Enhances the precision and depth of epidemiological analyses in complex disease studies.