Categorical data analysis /
"A classic in its own right, this book continues to provide an introduction to modern generalized linear models for categorical variables. The text emphasizes methods that are most commonly used in practical application, such as classical inferences for two- and three-way contingency tables, lo...
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| Language: | eng |
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Hoboken, N.J. : Wiley,
c201
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| _version_ | 1826454099320635392 |
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| author | 413711 Agresti, Alan |
| author_facet | 413711 Agresti, Alan |
| author_sort | 413711 Agresti, Alan |
| collection | OCEAN |
| description | "A classic in its own right, this book continues to provide an introduction to modern generalized linear models for categorical variables. The text emphasizes methods that are most commonly used in practical application, such as classical inferences for two- and three-way contingency tables, logistic regression, loglinear models, models for multinomial (nominal and ordinal) responses, and methods for repeated measurement and other forms of clustered, correlated response data. Chapter headings remain essentially with the exception of a new one on Bayesian inference for parametric models. Other major changes include an expansion of clustered data, new research on analysis of data sets with robust variables, extensive discussions of ordinal data, more on interpretation, and additional exercises throughout the book. R and SAS are now showcased as the software of choice. An author web site with solutions, commentaries, software programs, and data sets is available" |
| first_indexed | 2024-03-05T12:48:02Z |
| format | |
| id | KOHA-OAI-TEST:486005 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T12:48:02Z |
| publishDate | c201 |
| publisher | Hoboken, N.J. : Wiley, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:4860052020-12-19T17:17:56ZCategorical data analysis / 413711 Agresti, Alan Hoboken, N.J. : Wiley,c2013eng"A classic in its own right, this book continues to provide an introduction to modern generalized linear models for categorical variables. The text emphasizes methods that are most commonly used in practical application, such as classical inferences for two- and three-way contingency tables, logistic regression, loglinear models, models for multinomial (nominal and ordinal) responses, and methods for repeated measurement and other forms of clustered, correlated response data. Chapter headings remain essentially with the exception of a new one on Bayesian inference for parametric models. Other major changes include an expansion of clustered data, new research on analysis of data sets with robust variables, extensive discussions of ordinal data, more on interpretation, and additional exercises throughout the book. R and SAS are now showcased as the software of choice. An author web site with solutions, commentaries, software programs, and data sets is available"Includes bibliographical references and index"A classic in its own right, this book continues to provide an introduction to modern generalized linear models for categorical variables. The text emphasizes methods that are most commonly used in practical application, such as classical inferences for two- and three-way contingency tables, logistic regression, loglinear models, models for multinomial (nominal and ordinal) responses, and methods for repeated measurement and other forms of clustered, correlated response data. Chapter headings remain essentially with the exception of a new one on Bayesian inference for parametric models. Other major changes include an expansion of clustered data, new research on analysis of data sets with robust variables, extensive discussions of ordinal data, more on interpretation, and additional exercises throughout the book. R and SAS are now showcased as the software of choice. An author web site with solutions, commentaries, software programs, and data sets is available"PSZJBLMultivariate analysisURN:ISBN:9780470463635 (hbk.) |
| spellingShingle | Multivariate analysis 413711 Agresti, Alan Categorical data analysis / |
| title | Categorical data analysis / |
| title_full | Categorical data analysis / |
| title_fullStr | Categorical data analysis / |
| title_full_unstemmed | Categorical data analysis / |
| title_short | Categorical data analysis / |
| title_sort | categorical data analysis |
| topic | Multivariate analysis |
| work_keys_str_mv | AT 413711agrestialan categoricaldataanalysis |