Sinopse

An increasing number of social, behavioral and biomedical scientists, researchers in public health marketing, education, biology and agriculture are using statistical methods for categorizing data. To meet the needs of practitioners as well as students Agresti (statistics emeritus, U. of Florida) provides and introduction to the most important methods of performing categorical data analysis, covering contingency tables, generalized linear models, logistic regression, building and applying logistic regression models, multicategory logit models, loglinear models for contingency tables, models for matched pairs, modeling co-related or clustered responses, random effects in generalized linear mixed models and an historical tour of categorical data analysis. Agresti includes exercises and answers.

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