COLLEGE PARK, MD (January, 2016) Dr. Ji Seung Yang, an assistant professor in the Department of Human Development and Quantitative Methodology, has been awarded a $200,000 Statistical and Research Methodology grant by the U.S. Department of Educations Institute of Education Sciences to develop multilevel item bi-factor models..
Titled “Multilevel Item Bifactor Models with Semi-Nonparametric Latent Densities,” Dr. Yang’s project seeks to develop a better way to deal with measurement error in variables using latent variable modeling and to address the impact of non-normality in latent variable distributions.
According to the project’s description, predictors that contain measurement error yield attenuated correlation or regression coefficient estimates, which results in bias in treatment effect estimates. The attenuation problem gets worse with educational data, since class- or school-level variables are often calculated by simply averaging observed individual scores. But by applying a multilevel and multidimensional measurement model, the measurement error in the predictor can be more properly handled.
Currently available multilevel measurement models are limited to normally distributed latent variables. Dr. Yang’s research team will develop software that can run the necessary models for non-normally distributed latent variables. Then, the researchers will use simulation studies to investigate the extent to which various model facets lead to bias in the parameter estimates.
By the end of the project, the team expects to have released a user-friendly version of the software and to be working on disseminating the results of the research at conferences and in journals.
Dr. Ji Seung Yang is an assistant professor in the Department of Human Development and Quantitative Methodology’s Measurement, Statistics, and Evaluation (EDMS) program. Before joining the EDMS faculty in the fall of 2013, Dr. Yang was a postdoctoral researcher and lecturer at the University of California, Los Angeles (UCLA), where she received her Ph.D. in Advanced Quantitative Methods in Educational Research.
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