01641 a2200217 4500008004100000020001800041082001800059100001400077245005900091260003200150300001500182365001500197440004000212504005100252520102300303650002401326650002901350650001701379700001201396700001501408140323b2012 xxu||||| |||| 00| 0 eng d a9781439806241 a519.53 bT2A7 aTang, Wan aApplied categorical and count data analysiscTang, Wan c2012bCRC PressaBoca Raton axx, 363 p. aPNDb57.99 aTexts in statistical science series 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 analysis aCategories (Mathematics) aMathematics aHe, Hua aM. Tu, Xin