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Hierarchical Linear Models
Sun, April 16, 2:50 to 4:20pm CDT (2:50 to 4:20pm CDT), Chicago Marriott Downtown Magnificent Mile, Floor: 4th Floor, Belmont - Avenue BallroomSession Type: Paper Session
Abstract
Hierarchical Linear Models (HLM) continues to grow in use to address key questions in educational research. This HLM session provides four excellent papers that introduce new techniques that will continue to expand the use of this key methodology in educational research.
Sub Unit
Chair
Papers
A Comparison of Methods for Centering Covariates in Cross-Classified Random Effects Models - Young Ri Lee, University of Texas at Austin; Tasha Beretvas, University of Texas at Austin; James E. Pustejovsky, University of Wisconsin - Madison
Modeling Educational Inequalities at the Intersection of Multiple Social Categories: Introducing a Novel Multilevel Approach - Lena Keller, University of Potsdam; Oliver Lüdtke, Leibniz Institute for Science and Mathematics Education; Franzis Preckel, University of Trier; Martin Brunner, University of Potsdam
Robust Shrinkage Estimation of Effect Sizes via Bayesian Random-Effects Models for Meta-Analysis - Junok Kim, University of California - Los Angeles; Michael H. Seltzer, University of California - Los Angeles
Seeking New Alternatives to Recover Level 2 Covariates in Multilevel Models - Ismail Dilek, University of Iowa; Lesa Hoffman, University of Iowa