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008			150903s2009 xxu| o |||| 0|eng d
020			_a9780387096100 _9978-0-387-09610-0
024	7		_a10.1007/b12532 _2doi
035			_avtls000329700
039		9	_a201509031112 _bVLOAD _c201405070501 _dVLOAD _c201401311315 _dstaff _c201401311140 _dstaff _y201401291438 _zstaff _wmsplit0.mrc _x123
100	1		_aHagenaars, Jacques A. _eautor _9299859
245	1	0	_aMarginal Models : _bFor Dependent, Clustered, and Longitudinal Categorical Data / _cby Jacques A. Hagenaars, Marcel A. Croon, Wicher Bergsma.
264		1	_aNew York, NY : _bSpringer New York, _c2009.
300			_aXI, 268páginas, _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aStatistics for Social and Behavioral Sciences
500			_aSpringer eBooks
505	0		_aLoglinear Marginal Models -- Nonloglinear Marginal Models -- Marginal Analysis of Longitudinal Data -- Causal Analyses: Structural Equation Models and (Quasi-)Experimental Designs -- Marginal modeling with latent variables -- Conclusions, Extensions, and Applications.
520			_aMarginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles of marginal modeling and offers a wide range of possible applications. Marginal models are often the best choice for answering important research questions when dependent observations are involved, as the many real world examples in this book show. In the social, behavioral, educational, economic, and biomedical sciences, data are often collected in ways that introduce dependencies in the observations to be compared. For example, the same respondents are interviewed at several occasions, several members of networks or groups are interviewed within the same survey, or, within families, both children and parents are investigated. Statistical methods that take the dependencies in the data into account must then be used, e.g., when observations at time one and time two are compared in longitudinal studies. At present, researchers almost automatically turn to multi-level models or to GEE estimation to deal with these dependencies. Despite the enormous potential and applicability of these recent developments, they require restrictive assumptions on the nature of the dependencies in the data. The marginal models of this book provide another way of dealing with these dependencies, without the need for such assumptions, and can be used to answer research questions directly at the intended marginal level. The maximum likelihood method, with its attractive statistical properties, is used for fitting the models. This book has mainly been written with applied researchers in mind. It includes many real world examples, explains the types of research questions for which marginal modeling is useful, and provides a detailed description of how to apply marginal models for a great diversity of research questions. All these examples are presented on the book's website (www.cmm.st), along with user friendly programs. Wicher Bergsma is Senior Lecturer at the London School of Economics and Political Science. His current research interests are categorical data analysis, measurement of association, nonparametric regression, and maximum likelihood estimation. Marcel Croon is associate professor at Tilburg University. He is especially interested in measurement problems, structural equation modeling, latent variables, and random effect models. Jacques Hagenaars is full professor at Tilburg University and at present chair of the board of IOPS, the Dutch PhD School for Sociometrics and Psychometrics. His main research interests are research designs, longitudinal research, categorical data analysis and latent variable models.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aCroon, Marcel A. _eautor _9299860
700	1		_aBergsma, Wicher. _eautor _9299861
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387096094
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/b12532 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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