Multilevel statistical models /

This book provides a clear introduction to this important area of statistics. The author provides a wide of coverage of different kinds of multilevel models, and how to interpret different statistical methodologies and algorithms applied to such models. This 4th edition reflects the growth and inter...

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Bibliographic Details
Main Author: Goldstein, Harvey, 1939-
Format: eBook
Language:English
Published: Hoboken, N.J. : Wiley, 2011.
Edition:4th ed.
Series:Wiley series in probability and statistics.
Subjects:
Online Access:View fulltext via EzAccess
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100 1 |a Goldstein, Harvey,  |d 1939- 
245 1 0 |a Multilevel statistical models /  |c Harvey Goldstein. 
250 |a 4th ed. 
264 1 |a Hoboken, N.J. :  |b Wiley,  |c 2011. 
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490 1 |a Wiley series in probability and statistics 
504 |a Includes bibliographical references (pages 333-346) and indexes. 
505 0 |a Front Matter -- An Introduction to Multilevel Models -- The 2-level Model -- 3-level Models and more Complex Hierarchical Structures -- Multilevel Models for Discrete Response Data -- Models for Repeated Measures Data -- Multivariate Multilevel Data -- Latent Normal Models for Multivariate Data -- Multilevel Factor Analysis, Structural Equation and Mixture Models -- Nonlinear Multilevel Models -- Multilevel Modelling in Sample Surveys -- Multilevel Event History and Survival Models -- Cross-Classified Data Structures -- Multiple Membership Models -- Measurement Errors in Multilevel Models -- Smoothing Models for Multilevel Data -- Missing Data, Partially Observed Data and Multiple Imputation -- Multilevel Models with Correlated Random Effects -- Software for Multilevel Modelling. 
520 |a This book provides a clear introduction to this important area of statistics. The author provides a wide of coverage of different kinds of multilevel models, and how to interpret different statistical methodologies and algorithms applied to such models. This 4th edition reflects the growth and interest in this area and is updated to include new chapters on multilevel models with mixed response types, smoothing and multilevel data, models with correlated random effects and modeling with variance. 
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