Sarah D. Newton successfully defended her doctoral dissertation entitled, “Multilevel Model Selection and Effective Sample Size—In Information Criteria We Trust.” Congratulations, Dr. Newton!
Author: Newton, Sarah
Dakota Cintron Successfully Defends Doctoral Dissertation
Dakota Cintron successfully defended his doctoral dissertation entitled, “Statistical Estimation of Large Ordinal Factor Analysis Models.” Congratulations, Dr. Cintron!
RMME Community Members Discuss Research at NERA 2017
RMME Community members (now, both RMME PhD alumni), David Alexandro and Xiaowen Liu, discuss presented research at NERA 2017. Congratulations on this successful presentation, from the Research Methods, Measurement, & Evaluation Community!
Presenter: David Alexandro
Authors: Charles Martie, David Alexandro, William Estepar-Garcia, & Ajit Gopalakrishnan
Poster Presentation Title: Every Target and Milestone Matters: Developing Connecticut’s Evidence-Based Early Indication Tool (EIT)
Poster Abstract: Early warning systems typically focus on students’ dropout risk. The Connecticut State Department of Education extended this model to create the Early Indication Tool (EIT), a K-12 system that predicts student performance, identifies students who are at-risk of missing milestones and/or dropping out, and ultimately facilitates more timely interventions.