{"product_id":"logistic-regression-using-sas-theory-and-application-second-edition-hardcover","title":"Logistic Regression Using SAS: Theory and Application, Second Edition - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003ePaul D. Allison\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eIf you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul Allison's \u003ci\u003eLogistic Regression Using SAS: Theory and Application, Second Edition\u003c\/i\u003e, is for you  Informal and nontechnical, this book both explains the theory behind logistic regression, and looks at all the practical details involved in its implementation using SAS. Several real-world examples are included in full detail. This book also explains the differences and similarities among the many generalizations of the logistic regression model. The following topics are covered: binary logistic regression, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis, and Poisson regression. Other highlights include discussions on how to use the GENMOD procedure to do loglinear analysis and GEE estimation for longitudinal binary data. Only basic knowledge of the SAS DATA step is assumed. The second edition describes many new features of PROC LOGISTIC, including conditional logistic regression, exact logistic regression, generalized logit models, ROC curves, the ODDSRATIO statement (for analyzing interactions), and the EFFECTPLOT statement (for graphing nonlinear effects). Also new is coverage of PROC SURVEYLOGISTIC (for complex samples), PROC GLIMMIX (for generalized linear mixed models), PROC QLIM (for selection models and heterogeneous logit models), and PROC MDC (for advanced discrete choice models). \u003c\/p\u003e\u003cp\u003e This book is part of the SAS Press program.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003ePaul D. Allison is Professor of Sociology at the University of Pennsylvania, and President of Statistical Horizons LLC. He is the author of\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 348\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.81 x 11.02 x 8.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 20, 2018\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47212620382457,"sku":"9781635269093","price":132.41,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/YUI1R3pBb2NXMkt2WmRVSjkxK1Azdz09.webp?v=1768094730","url":"https:\/\/bookscloud.io\/products\/logistic-regression-using-sas-theory-and-application-second-edition-hardcover","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}