- Browse
Search
Browse By Day
Browse By Time
Browse By Person
Browse By Room
Browse By Unit
Browse By Session Type
Browse Sessions by Descriptor
Browse Papers by Descriptor
Browse Sessions by Research Method
Browse Papers by Research Method
- Information Menu
Search Tips
Annual Meeting Housing and Travel
- Navigation and Settings Menu
Personal Schedule
Change Preferences / Time Zone
Sign In
- Social Media Menu
Facebook
X (Twitter)
Matching and Selection in Observational Data
Sun, April 11, 2:30 to 3:30pm EDT (2:30 to 3:30pm EDT), Division D, Division D - Section 2 Roundtable SessionsSession Type: Roundtable Session
Abstract
This session focuses on analyzing observational data when matching of samples or selection of variables are necessary to make sound statistical inferences. Different methods were discussed and compared when various issues occurred in practical settings. Helpful recommendations and pros and cons were discussed as well.
Sub Unit
Chair
Papers
Difference-in-Differences, Propensity Score Matching, and Propensity Score Weighting in School-Level Natural Experiments - Peter Boedeker, Baylor College of Medicine
Propensity Score Analysis With Mismeasured Covariates - Huibin Zhang, University of Tennessee
The Effect of Lack of Measurement Invariance in Propensity Score Analysis With Latent Variables - Yongseok Lee, University of Florida; Walter L. Leite, University of Florida
What's in a Level? Investigating Propensity Score Methods for Effects on Hierarchical Linear Modeling Treatment Estimates - Alexandra Lane Stone, University of Connecticut - Storrs; Carla Evans, Center for Assessment
Statistical Inference After Variable Selection via Penalized Regression: Focusing on Variables Predicting Belonging to School - Jin Eun Yoo, Korea National University of Education; Minjeong Rho, Korea National University of Education