logo BDSP

Base documentaire


Votre avis nous intéresse

Le réseau BDSP met en oeuvre un projet d'innovation et d'amélioration de ses services, dans le souci constant de proposer des contenus de qualité adaptés aux besoins des utilisateurs.

Identifier de nouvelles sources de financements est la condition nécessaire pour assurer la poursuite et la pérennité de cet outil unique qu'est la BDSP, tout en le faisant évoluer.

Pour définir un nouveau modèle économique, nous avons besoin de votre avis : merci de répondre à notre enquête (temps estimé : 5 minutes).

Participer maintenant
Participer plus tard J'ai déjà participé

  1. A critical look at methods for handling missing covariates in epidemiologic regression analyses.

    Article - En anglais

    Epidemiologic studies often encounter missing covariate values.

    While simple methods such as stratification on missing-data status, conditional-mean imputation, and complete-subject analysis are commonly employed for handling this problem, several studies have shown that these methods can be biased under reasonable circumstances.

    The authors review these results in the context of logistic regression and present simulation experiments showing the limitations of the methods.

    The method based on missing-data indicators can exhibit severe bias even when the data are missing completely at random, and regression (conditional-mean) imputation can be inordinately sensitive to model misspecification.

    Even complete-subject analysis can outperform these methods.

    More sophisticated methods, such as maximum likelihood, multiple imputation, and weighted estimating equations, have been given extensive attention in the statistics literature.

    While these methods are superior to simple methods, they are not commonly used in epidemiology, no doubt due to their complexity and the lack of packaged software to apply these methods.

    The authors contrast the results of multiple imputation to simple methods in the analysis of a case-control study of endometrial cancer, and they find a meaningful difference in results for age at menarche.

    In general, the authors recommend that epidemiologists avoid using the missing-indicator method and use more sophisticated methods whenever a larg...

    Mots-clés Pascal : Epidémiologie, Méthodologie, Statistique, Régression logistique, Donnée manquante, Simulation ordinateur, Article synthèse

    Mots-clés Pascal anglais : Epidemiology, Methodology, Statistics, Logistic regression, Missing data, Computer simulation, Review

    Logo du centre Notice produite par :
    Inist-CNRS - Institut de l'Information Scientifique et Technique

    Cote : 96-0070742

    Code Inist : 002B30A01A1. Création : 199608.