Eye, Alexander von. creator Mun, Eun Young. text bibliography Electronic books. Electronic books. nju Hoboken, New Jersey Wiley [2013] 2013 monographic eng

electronic resource

1 online resource (xv, 450 pages) : illustrations "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"-- 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. 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. Includes bibliographical references and indexes. Log-linear models MATHEMATICS Probability & Statistics General MATHEMATICS Probability & Statistics Regression Analysis Log-linear models QA278 .E95 2013eb 519.5/36 MAT029000 Eye, Alexander von. Hoboken, New Jersey : Wiley, [2013] (DLC) 2012009791 (OCoLC)779259318 9781118391747 1118391748 9781118391778 1118391772 9781283977968 1283977966 http://onlinelibrary.wiley.com/book/10.1002/9781118391778 http://onlinelibrary.wiley.com/book/10.1002/9781118391778 N$T 130129 20171112084403.0 ocn825767800 eng