MARC Record from harvard_bibliographic_metadata

LEADER: 03356nam a2200349Ka 4500
001 011385232-0
005 20140910154234.0
008 080201s2008 nyua b 001 0 eng d
020 $a0387731830 (hbk.)
020 $a9780387731834 (hbk.)
035 0 $aocn191737715
040 $aSINIE$cSINIE
050 00 $aH61.25$b.H357 2008
245 00 $aHandbook of multilevel analysis /$cJan de Leeuw, Erik Meijer, editors ; foreword by Harvey Goldstein.
260 $aNew York :$bSpringer Verlag,$cc2008.
300 $axiii, 493 p. :$bill. ;$c24 cm.
504 $aIncludes bibliographical references and index.
505 0 $ato Multilevel Analysis -- Bayesian Multilevel Analysis and MCMC -- Diagnostic Checks for Multilevel Models -- Optimal Designs for Multilevel Studies -- Many Small Groups -- Multilevel Models for Ordinal and Nominal Variables -- Multilevel and Related Models for Longitudinal Data -- Non-Hierarchical Multilevel Models -- Multilevel Generalized Linear Models -- Missing Data -- Resampling Multilevel Models -- Multilevel Structural Equation Modeling.
520 $aMultilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the bio-medical sciences. The models used for this type of data are linear and nonlinear regression models that account for observed and unobserved heterogeneity at the various levels in the data. This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. The authors of the chapters are the leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is useful for empirical researchers in these fields. Prior knowledge of multilevel analysis is not required, but a basic knowledge of regression analysis, (asymptotic) statistics, and matrix algebra is assumed. Jan de Leeuw is Distinguished Professor of Statistics and Chair of the Department of Statistics, University of California at Los Angeles. He is former president of the Psychometric Society, former editor of the Journal of Educational and Behavioral Statistics, founding editor of the Journal of Statistical Software, and editor of the Journal of Multivariate Analysis. He is coauthor (with Ita Kreft) of Introducing Multilevel Modeling and a member of the Albert Gifi team who wrote Nonlinear Multivariate Analysis. Erik Meijer is Economist at the RAND Corporation and Assistant Professor of Econometrics at the University of Groningen. He is coauthor (with Tom Wansbeek) of the highly acclaimed book Measurement Error and Latent Variables in Econometrics.
650 0 $aSocial sciences$xResearch$xMathematical models.
650 0 $aMultilevel models (Statistics)
650 0 $aRegression analysis.
650 0 $aEconometrics.
650 0 $aEpidemiology.
650 0 $aMathematical statistics.
650 0 $aPsychometrics.
650 0 $aSocial sciences$xMethodology.
650 0 $aStatistics.
700 1 $aLeeuw, Jan De.
700 1 $aMeijer, Erik,$d1963-
988 $a20080213
906 $0OCLC