EdPolicyWorks Speaker Series: Tracy Sweet

ABSTRACT

Social network analysis focuses on the relationships among individuals in systems such as schools, and social network models are used to determine the effects of individual attributes on these relationships. Because of  the ill-defined dependence structure among network ties, one class of network models uses latent variables. Latent variable network models are also relatively simple to fit, allowing for a number of interesting extensions. In this talk, I will present two examples from my own research: a multilevel model mediation model and a latent variable model for social influence as well as discuss some future directions.

SPEAKER BIO

Tracy Sweet is an Associate Professor in the Measurement, Statistics and Evaluation program in the Department of Human Development and Quantitative Methodology. She completed her PhD in Statistics at Carnegie Mellon University and a MA in Mathematics at Morgan State University. Her research focuses on methods for social network analysis with particular focus on multilevel social network models, machine learning, and racial equity in data science and statistics. She serves as the Associate Director of Research for UMCP for the Maryland Longitudinal Data System Center and is currently overseeing projects applying data science and statistical methods to large-scale educational data.

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