03754nam 2200649 a 450 991046552320332120200520144314.03-11-026770-510.1515/9783110267709(CKB)2560000000079426(EBL)835473(OCoLC)772845239(SSID)ssj0000592032(PQKBManifestationID)11407071(PQKBTitleCode)TC0000592032(PQKBWorkID)10727767(PQKB)11590567(MiAaPQ)EBC835473(DE-B1597)173598(OCoLC)778827020(DE-B1597)9783110267709(Au-PeEL)EBL835473(CaPaEBR)ebr10527876(CaONFJC)MIL628137(EXLCZ)99256000000007942620111005d2012 uy 0engur|n|---|||||txtccrMultilevel models[electronic resource] applications using SAS /Jichuan Wang, Haiyi Xie, James H. FischerBerlin De Gruyter ;Boston Higher Education Pressc20121 online resource (274 p.)Description based upon print version of record.1-306-96886-0 3-11-026759-4 Includes bibliographical references and index. Frontmatter -- Preface / Wang, Jichuan / Xie, Haiyi / Fisher, James H. -- Contents -- Chapter 1. Introduction -- Chapter 2. Basics of linear multilevel models -- Chapter 3. Application of two-level linear multilevel models -- Chapter 4. Application of multilevel modeling to longitudinal data -- Chapter 5. Multilevel models for discrete outcome measures -- Chapter 6. Other applications of multilevel modeling and related issues -- References -- IndexInterest in multilevel statistical models for social science and public health studies has been aroused dramatically since the mid-1980s. New multilevel modeling techniques are giving researchers tools for analyzing data that have a hierarchical or clustered structure. Multilevel models are now applied to a wide range of studies in sociology, population studies, education studies, psychology, economics, epidemiology, and public health. This book covers a broad range of topics about multilevel modeling. The goal of the authors is to help students and researchers who are interested in analysis of multilevel data to understand the basic concepts, theoretical frameworks and application methods of multilevel modeling. The book is written in non-mathematical terms, focusing on the methods and application of various multilevel models, using the internationally widely used statistical software, the Statistics Analysis System (SAS®). Examples are drawn from analysis of real-world research data. The authors focus on twolevel models in this book because it is most frequently encountered situation in real research. These models can be readily expanded to models with three or more levels when applicable. A wide range of linear and non-linear multilevel models are introduced and demonstrated. Social sciencesResearchMathematical modelsMultilevel models (Statistics)Electronic books.Social sciencesResearchMathematical models.Multilevel models (Statistics)005.5/5SK 850rvkWang Jichuan960180Xie Haiyi1048698Fischer James H1048699MiAaPQMiAaPQMiAaPQBOOK9910465523203321Multilevel models2477148UNINA