03695oam 2200685I 450 991078158320332120230126202514.00-429-19160-X1-4987-4070-71-4398-1327-210.1201/b10850(CKB)2550000000064988(EBL)800943(OCoLC)756675740(SSID)ssj0000539327(PQKBManifestationID)11314720(PQKBTitleCode)TC0000539327(PQKBWorkID)10568628(PQKB)10733449(MiAaPQ)EBC800943(Au-PeEL)EBL800943(CaPaEBR)ebr10511313(CaONFJC)MIL692570(EXLCZ)99255000000006498820180331d2011 uy 0engur|n|---|||||txtccrMultivariate generalized linear mixed models using R /Damon M. Berridge, Robert CrouchleyBoca Raton, Fla. :CRC Press,2011.1 online resource (284 p.)A Chapman & Hall book.1-322-61288-9 1-4398-1326-4 Includes bibliographical references and indexes.Front Cover; Contents; List of Figures; List of Tables; List of Applications; List of Datasets; Preface; Acknowledgments; 1. Introduction; 2.Generalized linear models for continuous/interval scale data; 3. Generalized linear models for other types of data; 4. Family of generalized linear models; 5. Mixed models for continuous/interval scale data; 6. Mixed models for binary data; 7. Mixed models for ordinal data; 8. Mixed models for count data; 9. Family of two-level generalized linear models; 10. Three-level generalized linear models; 11. Models for multivariate data12. Models for duration and event history data13. Stayers, non-susceptibles and endpoints; 14. Handling initial conditions/state dependence in binary data; 15. Incidental parameters: an empirical comparison of fixed effects and random effects models; A. SabreR installation, SabreR commands, quadrature, estimation, endogenous effects; B. Introduction to R for Sabre; ReferencesTo provide researchers with the ability to analyze large and complex data sets using robust models, this book presents a unified framework for a broad class of models that can be applied using a dedicated R package (Sabre). The first five chapters cover the analysis of multilevel models using univariate generalized linear mixed models (GLMMs). The next few chapters extend to multivariate GLMMs and the last chapters address more specialized topics, such as parallel computing for large-scale analyses. Each chapter includes many real-world examples implemented using Sabre as well as exercises andR (Computer program language)Social sciencesResearchMathematical modelsSocial sciencesResearchStatistical methodsSocial sciencesResearchData processingMultivariate analysisR (Computer program language).Social sciencesResearchMathematical models.Social sciencesResearchStatistical methods.Social sciencesResearchData processing.Multivariate analysis.003/.35133Berridge Damon M.1564773Crouchley Robert1564774MiAaPQMiAaPQMiAaPQBOOK9910781583203321Multivariate generalized linear mixed models using R3834023UNINA