Handbook of Advanced Multilevel Analysis

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  • Format: Hardcover
  • Copyright: 2010-07-19
  • Publisher: Routledge

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Supplemental Materials

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This practical introduction helps readers apply multilevel techniques to their research. Noted as an accessible introduction, the book also includes advanced extensions making it useful as both an introduction and as a reference to students, researchers, and methodologists. Basic models and examples are discussed in non-technical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines. For example, readers will find data sets on stress in hospitals, GPA scores, survey responses, street safety, epilepsy, divorce, and sociometric scores, to name a few. The data sets are available on the website in SPSS, HLM, MLwiN, LISREL and/or Mplus files. Readers are introduced to both the multilevel regression model and multilevel structural models.Highlights of the second edition include:Two new chapters --one on Multilevel Models for Ordinal and Count Data (Ch. 7) and another on Multilevel Survival Analysis (Ch. 8).Thoroughly unpdated chapters on multilevel structural equation modeling that reflect the enormous technical progress of the last few years.The addition of some simpler examples to help the novice, but the more complex examples that combine more than one problem were retained.A new section on multivariate meta-analysis (Ch. 11).Expanded discussions of covariance structures across time and analyzingããlongitudinal data where noãtrendãis expected.Expanded chapter on Logistic Model for Dichotomous Data and Proportions with new estimation methods.An updated website at www.joophox.net/ with data sets for all the text examples and up to date screen shots and PowerPoint slides for Instructors.Ideal for introductory courses on multilevel modeling and/or ones that introduce this topic in some detail taught in a variety of disciplines including psychology, education, sociology, the health sciences, and business, ãthe advanced extensions also make this a favorite resource for researchers and methodologists in these disciplines. A basic understanding of ANOVA and multiple regression is assumed. The section on multilevel structural equation models assumes a basic understanding of SEM.

Table of Contents

Prefacep. vii
Multilevel Analysis: Where We Were and Where We Arep. 3
Multilevel Latent Variable Modeling (LVM)
Beyond Multilevel Regression Modeling: Multilevel Analysis in a General Latent Variable Frameworkp. 15
Multilevel IRT Modelingp. 41
Mixture Models for Multilevel Data Setsp. 59
Multilevel Models for Longitudinal Data
Panel Modeling: Random Coefficients and Covariance Structuresp. 85
Growth Curve Analysis Using Multilevel Regression and Structural Equation Modelingp. 97
Special Estimation Problems
Multilevel Analysis of Ordinal Outcomes Related to Survival Datap. 115
Bayesian Estimation of Multilevel Modelsp. 137
Bootstrapping in Multilevel Modelsp. 163
Multiple Imputation of Multilevel Datap. 173
Handling Omitted Variable Bias in Multilevel Models: Model Specification Tests and Robust Estimationp. 197
Explained Variance in Multilevel Modelsp. 219
Model Selection Based on Information Criteria in Multilevel Modelingp. 231
Optimal Design in Multilevel Experimentsp. 257
Specific Statistical Issues
Centering in Two-Level Nested Designsp. 285
Cross-Classified and Multiple-Membership Modelsp. 313
Dyadic Data Analysis Using Multilevel Modelingp. 335
Author Indexp. 371
Subject Indexp. 379
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