Leseprobe
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Log-Linear Modeling
Alexander von Eye, Eun-Young Mun
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Naturwissenschaften, Medizin, Informatik, Technik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik
Beschreibung
An easily accessible introduction to log-linear modeling fornon-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 anessential, introductory treatment of the subject, featuring manynew and advanced log-linear methods, models, and applications. The book begins with basic coverage of categorical data, andgoes on to describe the basics of hierarchical log-linear models aswell as decomposing effects in cross-classifications andgoodness-of-fit tests. Additional topics include: * The generalized linear model (GLM) along with popular methodsof coding such as effect coding and dummy coding * Parameter interpretation and how to ensure that the parametersreflect the hypotheses being studied * Symmetry, rater agreement, homogeneity of association, logisticregression, and reduced designs models Throughout the book, real-world data illustrate the applicationof 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 thecontext of hierarchical log-linear modeling. Log-Linear Modeling is an excellent book for courses oncategorical data analysis at the upper-undergraduate and graduatelevels. It also serves as an excellent reference for appliedresearchers in virtually any area of study, from medicine andstatistics to the social sciences, who analyze empirical data intheir everyday work.
Rezensionen
"This book provides an essential, easily accessibleintroductory treatment of log-linear modelling. . . The book iswritten at a level that should pose no major problems to studentsafter introductory statistics courses."
"It is an excellent book for courses on categorical dataanalysis at the upper-undergraduate and graduate levels. It alsoserves as an excellent reference for applied researchers invirtually any area of study, from medicine and statistics to thesocial sciences, who analyze empirical data in their everydaywork."
Kundenbewertungen
Psychologie, Psychological Methods, Research & Statistics, Psychologische Methoden, Forschung u. Statistik, Psychology, Datenanalyse, Statistik in den Sozialwissenschaften, Statistik, Categorical Data Analysis, Statistics, Statistics for Social Sciences, Kategorielle Datenanalyse