000			01481cam a22001934a 4500
020			_a9780470463635
082	0	0	_a519.535 _bAGR/C
100	1		_aAgresti, Alan.
245	1	0	_aCategorical data analysis
250			_a3rd ed.
260			_aHoboken, NJ : _bWiley, _cc2013.
300			_axvi, 714 p. : _bill. ;
490	0		_aWiley series in probability and statistics ;
520			_a"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"--
650		0	_aMultivariate analysis.
650		7	_aProbability & Statistics
650		7	_aStatistics
942			_cBK
999			_c37414 _d37414