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Session Type: Paper Session
This session includes papers with two different themes -- advances with multiple imputation of MLM data and comparisons of latent models and latent multilevel models.
Model-Based Multiple Imputation for Multilevel Analyses - Craig K. Enders, University of California - Los Angeles; Han Du, University of California - Los Angeles; Brian Keller, University of California - Los Angeles
Multiple Imputation of Nonnormal Level 2 Missingness in Multilevel Models - Yutang Xiong, University of Denver; Duan Zhang, University of Denver
Evaluating Latent Class Models When Ignoring and Accounting for Clustering - Yan Wang, University of Massachusetts - Lowell; Seang-Hwane Joo, ETS; Seok Joon Chun, South Dakota State University; Abeer A. Alamri, University of South Florida; Phil Seok Lee, George Mason University; Eunsook Kim, University of South Florida; Stephen E. Stark, University of South Florida
Studying Trajectories With Clustered Longitudinal Data: A Comparison Between Mixed-Effect Modeling and Multilevel Latent Growth Curve Modeling - Hsien-Yuan Hsu, University of Massachusetts Lowell; Jr-Hung Lin, National Chiao Tung University; Minjung Kim, The Ohio State University; Sandra T. Acosta, Texas A&M University - College Station