Categorical data analysis
Material type: TextSeries: Wiley series in probability and statisticsPublication details: Hoboken, NJ : Wiley, c2013Edition: 3rd edDescription: xvi, 714 p. : illISBN: 9780470463635 Subject(s): Multivariate analysis | Probability & Statistics | StatisticsDDC classification: 519.535 Summary: "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"--Item type | Current library | Collection | Call number | Status | Date due | Barcode |
---|---|---|---|---|---|---|
BK | Kannur University Central Library Stack | Stack | 519.535 AGR/C (Browse shelf (Opens below)) | Available | 37195 |
Browsing Kannur University Central Library shelves, Shelving location: Stack, Collection: Stack Close shelf browser (Hides shelf browser)
519.53 FIT/A Applied longitudinal analysis / | 519.53 SON/B Basic and advanced Bayesian structural equation modeling : with applications in the medical and behavioural sciences | 519.53 TAN/A Applied categorical and count data analysis / | 519.535 AGR/C Categorical data analysis | 519.535 HUS/E Exploratory multivariate analysis by example using R / | 519.535 WES/L Linear mixed models : a practical guide using statistical software | 519.536 CHA/R Regression analysis by example |
"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"--
There are no comments on this title.