This book appeals to researchers who work with nested data structures or repeated measures data, including biomed & health researchers, clinical/intervention researchers and developmental & educational psychologists. Also some potential as a grad lvl tex

Contents: Preface. R. Cudeck, S.H.C. du Toit, Nonlinear Multilevel Models for Repeated Measures Data. M. Seltzer, K. Choi, Sensitivity Analysis for Hierarchical Models: Downweighting and Identifying Extreme Cases Using the t Distribution. P.M. Bentler, J. Liang, Two-Level Mean and Covariance Structures: Maximum Likelihood via an EM Algorithm. B. Muthén, S-T. Khoo, D.J. Francis, C.K. Boscardin, Analysis of Reading Skills Development From Kindergarten Through First Grade: An Application of Growth Mixture Modeling to Sequential Processes. J.J. Hox, E.D. de Leeuw, Multilevel Models for Meta-Analysis. B. Jo, B.O. Muthén, Longitudinal Studies With Intervention and Noncompliance: Estimation of Causal Effects in Growth Mixture Modeling. E.R. Baumler, R.B. Harrist, S. Carvajal, Analysis of Repeated Measures Data. N. Bachmann, R. Hornung, The Development of Social Resources in a University Setting: A Multilevel Analysis. A. Fielding, Ordered Category Responses and Random Effects in Multilevel and Other Complex Structures. D. Hutchison, Bootstrapping the Effect of Measurement Errors on Apparent Aggregated Group-Level Effects. R. Ecob, G. Der, An Iterative Method for the Detection of Outliers in Longitudinal Growth Data Using Multilevel Models. K.J. Rowe, Estimating Interdependent Effects Among Multilevel Composite Variables in Psychosocial Research: An Example of the Application of Multilevel Structural Equation Modeling. S.P. Reise, N. Duan, Design Issues in Multilevel Studies.