Handbook of Multilevel Analysis / edited by Jan de Leeuw, Erik Meijer
| データ種別 | 電子ブック |
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| 出版者 | New York, NY : Springer New York |
| 出版年 | 2008 |
| 本文言語 | 英語 |
| 大きさ | XIV, 494 p : online resource |
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| 内容注記 | to 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 |
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| 一般注記 | Multilevel 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 |
| 著者標目 | Leeuw, Jan de editor Meijer, Erik editor SpringerLink (Online service) |
| 件 名 | LCSH:Mathematics LCSH:Epidemiology LCSH:Probabilities LCSH:Statistics LCSH:Econometrics LCSH:Social sciences LCSH:Psychometrics FREE:Mathematics FREE:Probability Theory and Stochastic Processes FREE:Statistical Theory and Methods FREE:Methodology of the Social Sciences FREE:Psychometrics FREE:Econometrics FREE:Epidemiology |
| 分 類 | DC23:519.2 |
| 巻冊次 | ISBN:9780387731865 
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| ISBN | 9780387731865 |
| URL | http://dx.doi.org/10.1007/978-0-387-73186-5 |
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