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Preface | p. vii |
Introduction | |
Multilevel Analysis: Where We Were and Where We Are | p. 3 |
Multilevel Latent Variable Modeling (LVM) | |
Beyond Multilevel Regression Modeling: Multilevel Analysis in a General Latent Variable Framework | p. 15 |
Multilevel IRT Modeling | p. 41 |
Mixture Models for Multilevel Data Sets | p. 59 |
Multilevel Models for Longitudinal Data | |
Panel Modeling: Random Coefficients and Covariance Structures | p. 85 |
Growth Curve Analysis Using Multilevel Regression and Structural Equation Modeling | p. 97 |
Special Estimation Problems | |
Multilevel Analysis of Ordinal Outcomes Related to Survival Data | p. 115 |
Bayesian Estimation of Multilevel Models | p. 137 |
Bootstrapping in Multilevel Models | p. 163 |
Multiple Imputation of Multilevel Data | p. 173 |
Handling Omitted Variable Bias in Multilevel Models: Model Specification Tests and Robust Estimation | p. 197 |
Explained Variance in Multilevel Models | p. 219 |
Model Selection Based on Information Criteria in Multilevel Modeling | p. 231 |
Optimal Design in Multilevel Experiments | p. 257 |
Specific Statistical Issues | |
Centering in Two-Level Nested Designs | p. 285 |
Cross-Classified and Multiple-Membership Models | p. 313 |
Dyadic Data Analysis Using Multilevel Modeling | p. 335 |
Author Index | p. 371 |
Subject Index | p. 379 |
Table of Contents provided by Ingram. All Rights Reserved. |
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The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.