01874 a2200253 4500008004100000020001800041082001800059100002200077245005900099260003200158300001500190365001500205440004800220504005100268520102300319650003101342650003601373650002501409700002001434700002301454942000701477999001901484952011701503140323b2012 xxu||||| |||| 00| 0 eng d a9781439806241 a519.53 bT2A7 aTang, Wan9195981 aApplied categorical and count data analysiscTang, Wan c2012bCRC PressaBoca Raton axx, 363 p. aPNDb57.99 aTexts in statistical science series9134911 aIncludes bibliographical references and index. aDeveloped from the authorsH graduate-level biostatistics course, Applied Categorical and Count Data Analysis explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without using rigorous mathematical arguments.The text covers classic concepts and popular topics, such as contingency tables, logistic models, and Poisson regression models, along with modern areas that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples and even adapt or extend the codes to fit data from their own studies.(http://www.crcpress.com/product/isbn/9781439806241) aRegression analysis927678 aCategories (Mathematics)994132 aMathematics 9194628 aHe, Hua9194629 aM. Tu, Xin9194630 cBK c166443d166443 001040708NFICaVSLbVSLcGENd2012-09-26eKushal Booksl3m4o519.53 T2A7p177093r2019-03-07s2018-11-27yBK