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  1. Random-effects regression models for clustered data with an example from smoking prevention research.

    Article - En anglais

    A random-effects regression model is proposed for analysis of clustered data.

    Unlike ordinary regression analysis of clustered data, random-effects regression models do not assume that each observation is independent but do assume that data within clusters are dependent to some degree.

    The degree of this dependency is estimated along with estimates of the usual model parameters, thus adjusting these effects for the dependency resulting from the clustering of the data.

    A maximum marginal likelihood solution is described, and available statistical software for the model is discussed.

    Mots-clés Pascal : Analyse amas, Effet aléatoire, Analyse régression, Estimation paramètre, Maximum vraisemblance, Modèle statistique, Analyse statistique, Prévention, Tabagisme, Milieu scolaire, Adolescent, Homme

    Mots-clés Pascal anglais : Cluster analysis, Random effect, Regression analysis, Parameter estimation, Maximum likelihood, Statistical model, Statistical analysis, Prevention, Tobacco smoking, School environment, Adolescent, Human

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

    Cote : 94-0600313

    Code Inist : 002B18B03. Création : 09/06/1995.