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[null,"1.","Record Nr.",null,"UNINA9910457693303321"]
[null,null,"Autore",null,"Berridge Damon M."]
[null,null,"Titolo",null,"Multivariate generalized linear mixed models using R / / Damon M. Berridge, Robert Crouchley"]
[null,null,"Pubbl/distr/stampa",null,"Boca Raton, Fla. : , : CRC Press, , 2011"]
[null,null,"ISBN",null,"0-429-19160-X"]
[{"$nulls":4},"1-4987-4070-7"]
[{"$nulls":4},"1-4398-1327-2"]
[null,null,"Descrizione fisica",null,"1 online resource (284 p.)"]
[null,null,"Disciplina",null,"003/.35133"]
[null,null,"Soggetti",null,"Social sciences - Research - Mathematical models"]
[{"$nulls":4},"Social sciences - Research - Statistical methods"]
[{"$nulls":4},"Social sciences - Research - Data processing"]
[{"$nulls":4},"Multivariate analysis"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","A Chapman & Hall book."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and indexes."]
[null,null,"Nota di contenuto",null,"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 data"]
[{"$nulls":4},"12. Models for duration and event history data13. Stayers, non-susceptibles and endpoints; 14. Handling initial conditions/state dependence in binary data; 15. Incidental parameters: an empirical comparison of fixed effects and random effects models; A. SabreR installation, SabreR commands, quadrature, estimation, endogenous effects; B. Introduction to R for Sabre; References"]
[null,null,null,"Sommario/riassunto","To provide researchers with the ability to analyze large and complex data sets using robust models, this book presents a unified framework for a broad class of models that can be applied using a dedicated R package (Sabre). The first five chapters cover the analysis of multilevel models using univariate generalized linear mixed models (GLMMs). The "]
[{"$nulls":4},"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 and"]