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008			130619s2013 fluad sb 001 0 eng d
020			_a9781439884720 (ebook : PDF)
040			_aBD-DhSAU _cBD-DhSAU
090			_aQA278 _b.A49737 2013
092			_a519.535 _bA538
245	0	0	_aAnalysis of mixed data _h[electronic resource] : _bmethods & applications / _cedited by Alexander R. de Leon, Keumhee Carri�ere Chough.
260			_aBoca Raton : _bCRC Press/Taylor & Francis Group, _c2013.
300			_axxvii, 234 p. : _bill.
504			_aIncludes bibliographical references (p. 209-229) and index.
505	0		_a1. Analysis of mixed data : an overview / by Alexander R. de Leon and Keumhee Carri�ere Chough -- 2. Combining univariate and multivariate random forests for enhancing predictions of mixed outcomes / by Abdessamad Dine, Denis Larocque, and Fran�cois Bellavance -- 3. Joint tests for mixed traits in genetic association studies / by Minjung Kwak, Gang Zheng, and Colin O. Wu -- 4. Bias in factor score regression and a simple solution / by Takahiro Hoshino and Peter M. Bentler -- 5. Joint modeling of mixed count and continuous longitudinal data / by Jian Kang and Ying Yang -- 6. Factorization and latent variable models for joint analysis of binary and continuous outcomes / by Armando Teixeira-Pinto and Jaroslaw Harezlak -- 7. Regression models for analyzing clustered binary and continuous outcomes under the assumption of exchangeability / by E. Olusegun George, Dale Bowman, and Qi An -- 8. Random effects models for joint analysis of repeatedly measured discrete and continuous outcomes / by Ralitza Gueorguieva -- 9. Hierarchical modeling of endpoints of different types with generalized linear mixed models / by Christel Faes -- 10. Joint analysis of mixed discrete and continuous outcomes via copula models / by Beilei Wu, Alexander R. de Leon, and Niroshan Withanage -- 11. Analysis of mixed outcomes in econometrics : applications in health economics / by David M. Zimmer -- 12. Sparse Bayesian modeling of mixed econometric data using data augmentation / by Helga Wagner and Regina T�uchler -- 13. Bayesian methods for the analysis of mixed categorical and continuous (incomplete) data / by Michael J. Daniels and Jeremy T. Gaskins.
520			_a"A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics. Carefully edited for smooth readability and seamless transitions between chaptersAll chapters follow a common structure, with an introduction and a concluding summary, and include illustrative examples from real-life case studies in developmental toxicology, economics, medicine and health, marketing, and genetics. An introductory chapter provides a 'wide angle' introductory overview and comprehensive survey of mixed data analysisBlending theory and methodology, this book illustrates concepts via data from different disciplines. Analysis of Mixed Data: Methods & Applications traces important developments, collates basic results, presents terminology and methodologies, and gives an overview of statistical research applications. It is a valuable resource to methodologically interested as well as subject matter-motivated researchers in many disciplines"-- _cProvided by publisher.
530			_aAlso available in print edition.
538			_aMode of access: World Wide Web.
650		0	_aMultivariate analysis.
655		7	_aElectronic books. _2lcsh
700	1		_aDe Leon, Alexander R.
700	1		_aChough, Keumhee Carri�ere.
776	1		_z9781439884713 (hardback : alk. paper)
856	4	0	_uhttp://marc.crcnetbase.com/isbn/9781439884720 _qapplication/PDF
999			_c11872 _d11871