Multilevel Modelling

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Overview

Data collected in the social sciences often have a multilevel or clustered structure. From this we often have research questions that are of a multilevel nature, and multilevel modeling is now widely used across health, economics, demography, education, and many other areas to analyze data clustered within units at higher levels. The editors of this essential four-volume set are among the leading figures of multilevel modeling, an approach which is at once cutting-edge and well established within research methods and the social sciences.

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Table of Contents

VOLUME 1: LINEAR MULTILEVEL MODELS: MODEL FORMULATION AND INTERPRETATION
Introduction
Multilevel Analysis - Tom A.B. Snijders
New Statistical Methods for Analyzing Social Structures: An introduction to multilevel models - Lindsay Paterson and Harvey Goldstein
Modeling Multilevel Data Structures - Marco Steenbergen and Bardford Jones
Context, Composition and Heterogeneity: Using multilevel models in health research - Craig Duncan, Kelwyn Jones and Graham Moon
Statistical and Substantive Inferences in Public Health: Issues in the application of multilevel models - Jeffrey B. Bingenheimer and Stephen W. Raudenbush
A Glossary for Multilevel Analysis - A.V. Diez Roux
Models for Longitudinal and Panel Data
Application of Hierarchical Linear Models to Assessing Change - Anthony S. Bryk and Stephen W. Raudenbush
The Design and Analysis of Longitudinal Studies of Development and Psychopathology in Context: Statistical models and methodological recommendations - John B. Willett, Judith D. Singer and Nina C. Martin
Panel Models in Sociological Research: Theory into practice - Charles N. Halaby
The Multilevel Approach to Repeated Measures for Complete and Incomplete Data - Cora J.M. Maas and Tom A.B. Snijders
Multilevel and Related Models for Longitudinal Data - Anders Skrondal and Sophia Rabe-Hesketh
Multilevel Models for Longitudinal Data - Fiona Steele
Higher-level Models
The Analysis of Longitudinal, Multilevel Data - Stephen W. Raudenbush
Big-Fish-Little-Pond Effect on Academic Self-concept - Herbert W. Marsh and Kit-Tai Hau
Between Versus Within Effects, Mean Centering, and Endogeneity
Separation of Individual-level and Cluster-level Covariate Effects in Regression Analysis of Correlated Data - Melissa D. Begg and Michael K. Parides
Causes, Problems and Benefits of Different Between and Within Effects in the Analysis of Clustered Data - Mari Palta and Chris Seplaki
Regressor and Random-effect Dependencies in Multilevel Models - Peter Ebbes, Ulf Böckenholt and Michel Wedel
Variance Explained
Modeled Variance in Two-level Models - Tom A.B. Snijders and Roel J. Bosker
Bayesian Measures of Explained Variance and Pooling in Multilevel (Hierarchical) Models - Andrew Gelman and Iain Pardoe
VOLUME 2: LINEAR MULTILEVEL MODELS: INFERENCE, DIAGNOSTICS AND DESIGN
Parameter Estimation
Estimation Procedures for Hierarchical Linear Models - H. Swaminathan and H.J. Rogers
Introduction to Multilevel Analysis - Jan de Leeuw and Erik Meijer
Assigning Values to Random Effects
Assigning Values to the Random Intercepts - Sophia Rabe-Hesketh and Anders Skrondal
That BLUP is a Good Thing: The estimation of random effects - G.K. Robinson
Model Diagnostics and Robustness
Outliers in Multilevel Data - Ian H. Langford and Toby Lewis
Diagnostic Checks for Multilevel Models - Tom A.B. Snijders and Johannes Berkhof
The Effect of Misspecifying the Random-effects Distribution in Linear Mixed Models for Longitudinal Data - Geert Verbeke and Emmanuel Lesaffre
Robustness of the Linear Mixed Model to Misspecified Error Distribution - Hélène Jacqmin-Gadda, Solenne Sibillot, Cécile Proust, Jean-Michel Molina and Rodolphe Thiébaut
Model Building and Inference
Testing and Model Specification - Tom A.B. Snijders and Roel J. Bosker
Hierarchical Linear Models - Stephen W. Raudenbush and Anthony S. Bryk
Variance Component Testing in Multilevel Models - Johannes Berkhof and Tom A.B. Snijders
Inference and Hierarchical Modelling in the Social Sciences - David Draper
Study Design, Power, and Sample Size
Power and Sample Size in Multilevel Linear Models - Tom A.B. Snijders
Statistical Analysis and Optimal Design for Cluster Randomized Trials - Stephen W. Raudenbush
Design Issues for Experiments in Multilevel Populations - Mirjam Moerbeek, Gerard J.P. van Breukelen and Martijn P.F. Berger
VOLUME 3: MULTILEVEL GENERALIZED LINEAR MODELS
Introduction
Multilevel Modeling of Binary Data - Guong Guo and Hongxin Zhao
Generalized Linear Mixed Models - Donald Hedeker
Generalized Linear Mixed Effects Models - Sophia Rabe-Hesketh and Anders Skrondal
Statistical Methods for Longitudinal and Clustered Designs with Binary Responses - John M. Neuhaus
Limited Dependent Variable Models Using Panel Data - G. S. Maddala
Ordered and Unordered Categorical Responses
A Mixed-effects Regression Model for Three-level Ordinal Response Data - Rema Raman and Donald Hedeker
Multilevel Logistic Regression for Polytomous Responses and Rankings - Anders Skrondal and Sophia Rabe-Hesketh
Hierarchical Models of Paired Comparison Data - Ulf Böckenholt
Survival and Counts
Random-effects Regression Analysis of Correlated Grouped-time Survival Data - Donald Hedeker, Ohidul Siddiqui and Frank Hu
The Random-effects Proportional Hazards Model with Grouped Survival Data: A comparison between the grouped continuous and continuation ratio versions - Leonardo Grilli
Chapter 10 of Hierarchical Linear Models: Applications and data analysis methods - Stephen W. Raudenbush and Anthony S. Bryk
Recent Developments in Count Data Modelling: Theory and application - Rainer Winkelmann and Klaus F. Zimmermann
Model Interpretation
Variance Partitioning in Multilevel Logistic Models that Exhibit Over-dispersion - William J. Browne, S.V. Subramanian, Kelwyn Jones and Harvey Goldstein
Appropriate Assessment of Neighborhood Effects on Individual Health: Integrating random and fixed effects in multilevel logistic regression - Klaus Larsen and Juan Merlo
Equivalence of Conditional and Marginal Regression Models for Clustered and Longitudinal Data - John Ritz and Donna Spiegelman
Estimation and Prediction
Statistical Inference in Generalized Linear Mixed Models: A review - Francis Tuerlinckx, Frank Rijmen, Geert Verbeke and Paul De Boeck
Misspecified Maximum Likelihood Estimates and Generalized Linear Mixed Models - Patrick J. Heagerty and Barbara F. Kurland
Prediction in Multilevel Generalized Linear Models - Anders Skrondal and Sophia Rabe-Hesketh
VOLUME 4: COMPLEX MODELS AND ISSUES
Nonlinear Mixed Models
Nonlinear Models for Repeated Measurement Data: An overview and update - Marie Davidian and David M. Giltinan
Complex Random Part
Heteroscedasticity and Complex Variation - Harvey Goldstein
Multilevel Models with Applications to Repeated Measures Data - Harvey Goldstein, Michael J. R. Healy and Jon Rasbash
Spatial Analysis - A. Leyland
Discrete and Nonnormal Random Effects
Analyzing Developmental Trajectories: A semiparametric, group-based approach - Daniel S. Nagin
Latent Class and Finite Mixture Models for Multilevel Data Sets - Jeroen K. Vermunt
A General Maximum Likelihood Analysis of Variance Components in Generalized Linear Models - Murray Aitkin
Multivariate Multilevel Models
Multilevel Analysis - J. Hox
Crossed Random Effects and Multiple Membership Models
A Crossed Random Effects Model for Unbalanced Data with Applications in Cross-sectional and Longitudinal Research - Stephen W. Raudenbush
Multiple Membership Multiple Classification (MMMC) Models - William J. Browne, Harvey Goldstein and Jon Rasbash
Resampling and Multiple Imputation
A Novel Bootstrap Procedure for Assessing the Relationship Between Class Size and Achievement - James R. Carpenter, Harvey Goldstein and Jon Rasbash
Multilevel Analysis of Messy Data - N.T. Longford
Multilevel Models with Latent Variables
Ecometrics: Toward a Science of Assessing Ecological Settings, with Application to the Systematic Social Observations of Neighborhoods - Stephen W. Raudenbush and Robert J. Sampson
Generalized Multilevel Structural Equation Modeling - Sophia Rabe-Hesketh, Anders Skrondal and Andrew Pickles
Multilevel Models for Complex Survey Data
Multilevel Modeling of Complex Survey Data - Sophia Rabe-Hesketh and Anders Skrondal
Mixed Responses or Multiple Process Models
Model-based Approaches to Analyzing Incomplete Repeated Measures and Failure Time Data - Joseph W. Hogan and Nan M. Laird
The Effect of Physician Advice on Alcohol Consumption: Count data regression with an endogenous treatment effect - Donald S. Kenkel and Joseph V. Terza
Simultaneous Equations for Hazards-marriage Duration and Fertility Timing - Lee A. Lillard

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