Incomplete Data Analysis and Latent Variable Model

An Invited-Paper Session of
the Institute of Mathematical Statistics Asia-Pacific Regional Meeting (IMS-APRM 2012)
2-4 Juny 2012, Tokyo, JAPAN

Session day: ?? ??, 2012
Session time: ** hours
Organizer: Yutaka Kano (Osaka University)
Chair: Kosuke Imai (Princeton University)

Session Program

Jingheng Cai (Sun Yat-sen University, China) and Xinyuan Song (The Chinese University of Hong Kong, HK): A Bayesian analysis of mixtures in structural equation models with nonignorable missing data
Ke-Hai Yuan (University of Notre Dame, USA) Xin Tong (University of Notre Dame, USA), and Zhiyong Zhang (University of Notre Dame, USA): Bias and Efficiency for SEM with Missing Data and Auxiliary Variables: Robust Method versus Normal Distribution Based ML
John W. Graham (The Pennsylvania State University, USA): Simulation methods for structural equation modeling with missing data
Yutaka Kano (Osaka University, Japan): NMARness and approximate population bias of the direct MLE in the analysis of missing data

This session is partly financially supported by the Grant-in-Aid for Scientific Research (B) #22300096 and Grant-in-Aid for Challenging Exploratory Research #23650145 from the Japan Society for the Promotion of Science.

Contents

Incomplete Data Analysis and Latent Variable Model