Generalized Linear Models in Family Studies.

Generalized linear models (GLMs), as defined by J. A. Nelder and R. W. M. Wedderburn (1972), unify a class of regression models for categorical, discrete, and continuous response variables. As an extension of classical linear models, GLMs provide a common body of theory and methodology for some seem...

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Publicado en:Journal of Marriage & Family Vol. 67; no. 4; pp. 1029 - 1048
Autor principal: Wu, Zheng
Formato: Artículo
Publicado: Wiley-Blackwell November 2005
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        au: Wu, Zheng
      su:
        Families -- Research
        Linear statistical models
        Family studies
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          Families -- Research
          Linear statistical models
          Family studies
      ab: Generalized linear models (GLMs), as defined by J. A. Nelder and R. W. M. Wedderburn (1972), unify a class of regression models for categorical, discrete, and continuous response variables. As an extension of classical linear models, GLMs provide a common body of theory and methodology for some seemingly unrelated models and procedures, such as the logistic, Poisson, and probit models, that are increasingly used in family studies. This article provides an overview of the principle and the key components of GLMs, such as the exponential family of distributions, the linear predictor, and the link function. To illustrate the application of GLMs, this article uses Canadian national survey data to build an example focusing on the number of close friends among older adults. The article concludes with a discussion of the strengths and weaknesses of GLMs. Reprinted by permission of the publisher.
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    language: English
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