LEADER 03549nam 2200637 450 001 9910463113103321 005 20200520144314.0 010 $a1-118-71085-1 010 $a1-118-71094-0 035 $a(CKB)2670000000354468 035 $a(EBL)1168529 035 $a(OCoLC)840466744 035 $a(SSID)ssj0000873336 035 $a(PQKBManifestationID)11560556 035 $a(PQKBTitleCode)TC0000873336 035 $a(PQKBWorkID)10866827 035 $a(PQKB)11351228 035 $a(MiAaPQ)EBC1168529 035 $a(JP-MeL)3000065395 035 $a(PPN)188189394 035 $a(Au-PeEL)EBL1168529 035 $a(CaPaEBR)ebr10867993 035 $a(CaONFJC)MIL604419 035 $a(EXLCZ)992670000000354468 100 $a20140513h20132013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aCategorical data analysis /$fAlan Agresti 205 $a3rd ed. 210 1$aHoboken, New Jersey :$cWiley-Interscience,$d2013. 210 4$dİ2013 215 $a1 online resource (1581 p.) 225 1 $aWiley Series in Probability and Statistics 300 $aDescription based upon print version of record. 311 $a0-470-46363-5 320 $aIncludes bibliographical references and indexes. 327 $aCover; Half Title page; Title page; Copyright page; Dedication; Preface; Chapter 1: Introduction: Distributions and Inference for Categorical Data; 1.1 Categorical Response Data; 1.2 Distributions for Categorical Data; 1.3 Statistical Inference for Categorical Data; 1.4 Statistical Inference for Binomial Parameters; 1.5 Statistical Inference for Multinomial Parameters; 1.6 Bayesian Inference for Binomial and Multinomial Parameters; Notes; Exercises; Chapter 2: Describing Contingency Tables; 2.1 Probability Structure for Contingency Tables; 2.2 Comparing Two Proportions 327 $aChapter 4: Introduction to Generalized Linear Models4.1 The Generalized Linear Model; 4.2 Generalized Linear Models for Binary Data; 4.3 Generalized Linear Models for Counts and Rates; 4.4 Moments and Likelihood for Generalized Linear Models; 4.5 Inference and Model Checking for Generalized Linear Models; 4.6 Fitting Generalized Linear Models; 4.7 Quasi-Likelihood and Generalized Linear Models; Notes; Exercises; Chapter 5: Logistic Regression; 5.1 Interpreting Parameters in Logistic Regression; 5.2 Inference for Logistic Regression; 5.3 Logistic Models with Categorical Predictors 327 $aChapter 9: Loglinear Models for Contingency Tables 330 $aPraise for the Second Edition ""A must-have book for anyone expecting to do research and/or applications in categorical data analysis.""-Statistics in Medicine ""It is a total delight reading this book.""-Pharmaceutical Research ""If you do any analysis of categorical data, this is an essential desktop reference.""-Technometrics The use of statistical methods for analyzing categorical data has increased dramatically, particularly in the biomedical, social sciences, and financial industries. Responding to new developments, 410 0$aWiley series in probability and statistics. 606 $aMultivariate analysis 608 $aElectronic books. 615 0$aMultivariate analysis. 676 $a519.5/35 700 $aAgresti$b Alan$0103037 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910463113103321 996 $aGroup-analytic psychotherapy, method and principles$91400706 997 $aUNINA