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Log-linear modeling : concepts, interpretation, and application /

"Over the past ten years, there have been many important advances in log-linear modeling, including the specification of new models, in particular non-standard models, and their relationships to methods such as Rasch modeling. While most literature on the topic is contained in volumes aimed at...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Eye, Alexander von
Otros Autores: Mun, Eun Young
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, New Jersey : Wiley, [2013]
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Eye, Alexander von. 
245 1 0 |a Log-linear modeling :  |b concepts, interpretation, and application /  |c Alexander von Eye, Michigan State University, Department of Psychology, East Lansing, MI, Eun-Young Mun, Rutgers, the State University of New Jersey, Center for Alcohol Studies, Piscataway, New Jersey. 
260 |a Hoboken, New Jersey :  |b Wiley,  |c [2013] 
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520 |a "Over the past ten years, there have been many important advances in log-linear modeling, including the specification of new models, in particular non-standard models, and their relationships to methods such as Rasch modeling. While most literature on the topic is contained in volumes aimed at advanced statisticians, Applied Log-Linear Modeling presents the topic in an accessible style that is customized for applied researchers who utilize log-linear modeling in the social sciences. The book begins by providing readers with a foundation on the basics of log-linear modeling, introducing decomposing effects in cross-tabulations and goodness-of-fit tests. Popular hierarchical log-linear models are illustrated using empirical data examples, and odds ratio analysis is discussed as an interesting method of analysis of cross-tabulations. Next, readers are introduced to the design matrix approach to log-linear modeling, presenting various forms of coding (effects coding, dummy coding, Helmert contrasts etc.) and the characteristics of design matrices. The book goes on to explore non-hierarchical and nonstandard log-linear models, outlining ten nonstandard log-linear models (including nonstandard nested models, models with quantitative factors, logit models, and log-linear Rasch models) as well as special topics and applications. A brief discussion of sampling schemes is also provided along with a selection of useful methods of chi-square decomposition. Additional topics of coverage include models of marginal homogeneity, rater agreement, methods to test hypotheses about differences in associations across subgroup, the relationship between log-linear modeling to logistic regression, and reduced designs. Throughout the book, Computer Applications chapters feature SYSTAT, Lem, and R illustrations of the previous chapter's material, utilizing empirical data examples to demonstrate the relevance of the topics in modern research"--  |c Provided by publisher 
504 |a Includes bibliographical references and indexes. 
588 0 |a Print version record. 
505 0 |a Basics of Hierarchical Log-Linear Models -- Effects in a Table -- Goodness-of-Fit -- Hierarchical Log-Linear Models and Odds Ratio Analysis -- Computations I: Basic Log-Linear Modeling -- The Design Matrix Approach -- Parameter Interpretation and Significance Tests -- Computations II: Design Matrices and Poisson GLM -- Nonhierarchical and Nonstandard Log-Linear Models -- Computations III: Nonstandard Models -- Sampling Schemes and Chi-Square Decomposition -- Symmetry Models -- Log-Linear Models of Rater Agreement -- Comparing Associations in Subtables: Homogeneity of Associations -- Logistic Regression and Other Logit Models -- Reduced Designs -- Computations IV: Additional Models. 
546 |a English. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Log-linear models. 
650 6 |a Modèles log-linéaires. 
650 7 |a MATHEMATICS  |x Probability & Statistics  |x General.  |2 bisacsh 
650 7 |a MATHEMATICS  |x Probability & Statistics  |x Regression Analysis.  |2 bisacsh 
650 7 |a Log-linear models  |2 fast 
700 1 |a Mun, Eun Young. 
758 |i has work:  |a Loglinear modeling (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCGXtPFtKfVKg4hw87cFqcP  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Eye, Alexander von.  |t Log-linear modeling.  |d Hoboken, New Jersey : Wiley, [2013]  |z 9781118146408  |w (DLC) 2012009791  |w (OCoLC)779259318 
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