Categorical Data Analysis Using SAS(3rd) 无水印原版pdf

Categorical Data Analysis Using SAS(3rd) 英文无水印原版pdf 第3版 pdf所有页面使用FoxitReader、PDFXChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书
Stokes, Maura E, Charles S Davis, and Gary G. Koch. Categorical Data Analysis Using SAS. Third Edition. Copyright o 2012, SAS Institute InC, Cary, North Carolina, USA. ALL RIGHTS RESERVED For additional SAS resources, visit support. sas. com/bookstore Contents pter 1. Introduction Chapter 2. The 2 x 2 Table Chapter 3. Sets of 22 Tables Chapter 4. 2 x r and s 2 Tables Chapter 5. The x r Table 107 Chapter 6. Sets of s x r Tables 141 Chapter 7. Nonparametric Methods 175 Chapter 8. Logistic Regression I: Dichotomous Response 189 hapter 9. Logistic Regression II: Polytomous Response 259 Chapter 10. Conditional logistic regression 297 Chapter ll. Quantal Response Data Analysis 345 Chapter 12. Poisson regression and related loglinear models 373 Chapter 13. Categorized TimetoEvent Data Chapter 14. Weighted Least Squares 427 Chapter 15. Generalized Estimating Equations 487 References 557 Index 573 Stokes, Maura E, Charles S Davis, and Gary G. Koch. Categorical Data Analysis Using SAS. Third Edition. Copyright o 2012, SAS Institute InC, Cary, North Carolina, USA. ALL RIGHTS RESERVED For additional SAS resources, visit support. sas. com/bookstore Stokes, Maura E, Charles S Davis, and Gary G. Koch. Categorical Data Analysis Using SAS. Third Edition. Copyright o 2012, SAS Institute InC, Cary, North Carolina, USA. ALL RIGHTS RESERVED For additional SAS resources, visit support. sas. com/bookstore Preface to the third edition The third edition accomplishes several purposes. First, it updates the use of sas software to current practices. Since the last edition was published more than 10 years ago, numerous sets of example statements have been modified to reflect best applications of SaS/Stat software Second, the material has been expanded to take advantage of the many graphs now provided by SAS/STAT Software through ODS Graphics. Beginning with SAS/STAT 9.3. these graphs are available with SASISTaTno other product license is required(a sas/GraPh license was required for previous releases). Graphs displayed in this edition include ● mosaic plots effect plot odds ratio plots predicted cumulative proportions plot regression diagnostic plots ● agreement plots Third, the book has been updated and reorganized to reflect the evolution of categorical data analysis strategies. The previous Chapter 14,"Repeated Measurements Using Weighted Least Squares, has been combined with the previous Chapter 13, "Weighted Least Squares, to create the current Chapter 14, "Weighted Least Squares. The material previously in Chapter 16 Loglinear Models, is found in the current Chapter 12, Poisson Regression and related loglinear Models. The material in Chapter 10, " Conditional Logistic Regression, has been rewritten, and Chapter 8, "Logistic Regression I: Dichotomous Response, and Chapter 9, " Logistic Regression II: Polytomous Response, have been expanded. In addition, the previous Chapter 16, Categorized TimetoEvent Data ' is the current Chapter 13 Numerous additional techniques are covered in this edition including e incidence density ratios and their confidence intervals additional confidence intervals for difference of proportions exact Poisson regression e difference measures to reflect direction of association in sets of tables partial proportional odds model use of the QiC statistic in gEE analysis Stokes, Maura E, Charles S Davis, and Gary G. Koch. Categorical Data Analysis Using SAS. Third Edition. Copyright o 2012, SAS Institute InC, Cary, North Carolina, USA. ALL RIGHTS RESERVED For additional SAS resources, visit support. sas. com/bookstore e odds ratios in the presence of interactions e Firth penalized likelihood approach for logistic regression In addition, miscellaneous revisions and additions have been incorporated throughout the book However, the scope of the book remains the same as described in Chapter l," Introduction Computing Details The examples in this third edition were executed with SAS/STAT 12. 1, although the revision was largely based on SAS/STAT 9.3. The features specific to SAS/STAT 12. 1 are mosaic plots in the FreQ procedure partial proportional odds model in the LOGistiC procedure Miettinen Nurminen confidence limits for proportion differences in PROC FREQ headings for the estimates from the FIRTH option in PROC LOGISTIC Because of limited space, not all of the output that is produced with the example sas code is shown Generally, only the output pertinent to the discussion is displayed. An ODS SELECT statement is sometimes used in the example code to limit the tables produced. The ODs gRAPHICs on and ODS GRAPHICS OFF statements are used when graphs are produced. However, these statements are not needed when graphs are produced as part of the sas windowing environment beginning with Sas9.3. Also, the graphs produced for this book were generated with the STYlE=JOURNAL option of ods because the book does not feature color For More Information Thewebsitehttp://www.sas.com/catbookcontainsfurtherinformationthatpertainsto topics in the book, including data(where possible)and errata Acknowledgments We are grateful to the many people who have contributed to this revision. Bob Derr, Amy Herring, Michael Hussey, Diana Lam, Siying Li, Michela Osborn, Ashley Lauren Paynter, Margaret Polinkovsky, John Preisser, David Schlotzhauer, Todd schwartz, Valerie smith, Daniela Soltres Alvarez, Donna Watts, Catherine Wiener, Laura Elizabeth Weiner, and Laura Zhou provided reviews, suggestions, proofing, and numerous other contributions that are greatl y appreciated Stokes, Maura E, Charles S Davis, and Gary G.Koch. Categorical Data Analysis Using SASO. Third Edition Copyright 2012, SAS Institute InC, Cary, North Carolina, USA. ALL RIGHTS RESERVED For additional SAS resources, visit support. sas. com/bookstore And of course, we remain thankful to those persons who contributed to the earlier editions They include Diane Catellier Sonia davis. Bob derr. William Duckworth Il. Suzanne edwards. Stuart Gansky, Greg Goodwin, Wendy greene, Duane Hayes, Allison Kinkead, Gordon Johnston, Lisa La vange. antonio pedrosodeLima. Annette Sanders John Preisser. David Schlotzhauer. Todd Schwartz, Dan Spitzner, Catherine Tangen, Lisa Tomasko, Donna Watts, Greg Weier, and ozkan Zengin Anne baxter and ed huddleston edited this book Tim Arnold provided documentation programming support Stokes, Maura E, Charles S Davis, and Gary G. Koch. Categorical Data Analysis Using SAS. Third Edition. Copyright o 2012, SAS Institute InC, Cary, North Carolina, USA. ALL RIGHTS RESERVED For additional SAS resources, visit support. sas. com/bookstore Stokes, Maura E, Charles S Davis, and Gary G. Koch. Categorical Data Analysis Using SAS. Third Edition. Copyright o 2012, SAS Institute InC, Cary, North Carolina, USA. ALL RIGHTS RESERVED For additional SAS resources, visit support. sas. com/bookstore Chapter 1 Introduction Contents 1.1 Overview 1. 2 Scale of measurement 1.3 Sampling Framework 1.4 Overview of Analysis Strategies·.··: 1. 4.1 Randomization methods 1. 4.2 Modeling strategies 245668 1. 5 Working with Tables in Sas Software 1.6 USing This Book 13 1.1 Overview Data analysts often encounter response measures that are categorical in nature; their outcomes reflect categories of information rather than the usual interval scale. Frequently, categorical data are presented in tabular form, known as contingency tables. Categorical data analysis is concerned with the analysis of categorical response measures regardless of whether any accompanying explanatory variables are also categorical or are continuous. This book discusses hypothesis testing strategies for the assessment of association in contingency tables and sets of contingency tables. It also discusses various modeling strategies available for describing the nature of the association between a categorical response measure and a set of explanatory variables An important consideration in determining the appropriate analysis of categorical variables is their scale of measurement Section 1.2 describes the various scales and illustrates them with data sets used in later chapters. Another important consideration is the sampling framework that produced the data; it determines the possible analyses and the possible inferences. Section 1.3 describes the typical sampling frameworks and their ramifications. Section 1. 4 introduces the various analysis strategies discussed in this book and describes how they relate to one another It also discusses the target populations generally assumed for each type of analysis and what types of inferences you are able to make to them. Section 1. 5 reviews how SaS software handles contingency tables and other forms of categorical data. Finally, Section 1.6 provides a guide to the material in the book for various types of readers, including indications of the difficulty level of the chapters Stokes, Maura E, Charles S Davis, and Gary G. Koch. Categorical Data Analysis Using SAS. Third Edition. Copyright o 2012, SAS Institute InC, Cary, North Carolina, USA. ALL RIGHTS RESERVED For additional SAS resources, visit support. sas. com/bookstore

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