The Sage Handbook of Multilevel Modeling

Herausgeber: Scott, Marc A; Marx, Brian D; Simonoff, Jeffrey S

• Gebundenes Buch

Produktbeschreibung

Leading contributors combine practical pieces with overviews of the state of the art in the field, making this handbook essential reading for any student or researcher looking to apply multilevel techniques in their own research

Produktdetails

• Verlag: Sage Publications Ltd
• Seitenzahl: 696
• Erscheinungstermin: 19. September 2013
• Englisch
• Abmessung: 254mm x 177mm x 50mm
• Gewicht: 1384g
• ISBN-13: 9780857025647
• ISBN-10: 0857025643
• Artikelnr.: 37039496

Inhaltsangabe

Notes on Contributors
Preface
Multilevel Modeling - Jeffrey S Simonoff, Marc A Scott and Brian D Marx
PART ONE: MULTILEVEL MODEL SPECIFICATION AND INFERENCE
The Multilevel Model Framework - Jeff Gill and Andrew Womack
Multilevel Model Notation - Establishing the Commonalities - Marc A Scott,
Patrick E Shrout and Sharon L Weinberg
Likelihood Estimation in Multilevel Models - Harvey Goldstein
Bayesian Multilevel Models - Ludwig Fahrmeir, Thomas Kneib, and Stefan Lang
The Choice between Fixed and Random Effects - Zac Townsend,Jack Buckley,
Masataka Harada and Marc A Scott
Centering Predictors and Contextual Effects - Craig K Enders
Model Selection for Multilevel Models - Russell Steele
Generalized Linear Mixed Models - Overview - Geert Verbeke and Geert
Molenberghs
Longitudinal Data Modeling - Nan M Laird and Garrett M Fitzmaurice
Complexities in Error Structures Within Individuals - Vicente Núnez-Antón
and Dale L Zimmerman
Design Considerations in Multilevel Studies - Gerard van Breukelen and
Mirjam Moerbeek
Multilevel Models and Causal Inference - Jennifer Hill
PART TWO: VARIATIONS AND EXTENSIONS OF THE MULTILEVEL MODEL
Multilevel Functional Data Analysis - Ciprian M Crainiceanu, Brian S Caffo
and Jeffrey S Morris
Nonlinear Models - Lang Wu and Wei Liu
Generalized Linear Mixed Models: Estimation and Inference - Charles E
McCulloch and John M Neuhaus
Categorical Response Data - Jeroen Vermunt
Smoothing and Semiparametric Models - Jin-Ting Zhang
Penalized Splines and Multilevel Models - Göran Kauermann and Torben
Kuhlenkasper
Hierarchical Dynamic Models - Marina Silva Paez and Dani Gamerman
Mixture and Latent Class Models in Longitudinal and Other Settings - Ryan P
Browne and Paul D McNicholas
Multivariate Response Data - Helena Geys and Christel Faes
PART THREE: PRACTICAL CONSIDERATIONS IN MODEL FIT AND SPECIFICATION
Robust Methods for Multilevel Analysis - Joop Hox and Rens van de Schoot
Missing Data - Geert Molenberghs and Geert Verbeke
Lack of Fit, Graphics, and Multilevel Model Diagnostics - Gerda Claeskens
Multilevel Models: Is GEE a Robust Alternative in the Presence of Binary
Endogenous Regressors? - Robert Crouchley
Software for Fitting Multilevel Models - Andrzej T Galecki and Brady T West
PART FOUR: SELECTED APPLICATIONS
Meta-Analysis - Larry V Hedges and Kimberly S Maier
Modeling Policy Adoption and Impact with Multilevel Methods - James E
Monogan III
Multilevel Models in the Social and Behavioral Sciences - David Rindskopf
Survival Analysis and the Frailty Model: The effect of education on
survival and disability for older men in England and Wales - Ardo van den
Hout and Brian D M Tom
Point-Referenced Spatial Modeling - Andrew O Finley and Sudipto Banerjee
Market Research and Preference Data - Adam Sagan
Multilevel Modeling for Scoial Networks and Relational Data - Marijtje A J
Van Duijn
Name Index
Subject Index