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e-book

Log-Linear Modeling (Cód: 9299176)

Eye, Alexander Von; Eun-Young Mun

Wiley (Digital)

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Log-Linear Modeling

R$175,50

Descrição

An easily accessible introduction to log-linear modeling for non-statisticians Highlighting advances that have lent to the topic's distinct, coherent methodology over the past decade, Log-Linear Modeling: Concepts, Interpretation, and Application provides an essential, introductory treatment of the subject, featuring many new and advanced log-linear methods, models, and applications. The book begins with basic coverage of categorical data, and goes on to describe the basics of hierarchical log-linear models as well as decomposing effects in cross-classifications and goodness-of-fit tests. Additional topics include: The generalized linear model (GLM) along with popular methods of coding such as effect coding and dummy coding Parameter interpretation and how to ensure that the parameters reflect the hypotheses being studied Symmetry, rater agreement, homogeneity of association, logistic regression, and reduced designs models Throughout the book, real-world data illustrate the application of models and understanding of the related results. In addition, each chapter utilizes R, SYSTAT®, and §¤EM software, providing readers with an understanding of these programs in the context of hierarchical log-linear modeling. Log-Linear Modeling is an excellent book for courses on categorical data analysis at the upper-undergraduate and graduate levels. It also serves as an excellent reference for applied researchers in virtually any area of study, from medicine and statistics to the social sciences, who analyze empirical data in their everyday work.

Características

Peso 0.00 Kg
Produto sob encomenda Sim
Marca Wiley (Digital)
Idioma 337
Acabamento e-book
Territorialidade Internacional
Formato Livro Digital Epub
Gratuito Não
Proteção Drm Sim
Início da Venda 08/03/2016
Código do Formato Epub
Cód. Barras 9781118391761
Número da edição 1
Ano da Publicação 114
AutorEye, Alexander Von; Eun-Young Mun