Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…

This study was conducted to systematically track and benchmark upper primary school students' ESL reading comprehension ability and subsequently generate data at the micro and macro levels according to individual achievement, school location, gender and ethnicity at the school, district, state and national levels. The main intention of this…

Peter Wylie is a man of many contradictions: a statistician and a storyteller, an introvert who loves an audience, and a self-described data geek with a passion for his work and the people it helps. Wylie is one of the pioneers of predictive modeling, the statistical analysis that uses data to drive educational institutions and nonprofits toward…

Increased demands for colleges and universities to engage in outcomes assessment for accountability purposes have accelerated the need to bridge the gap between higher education practice and the fields of measurement, assessment, and evaluation. The "Handbook on Measurement, Assessment, and Evaluation in Higher Education" provides higher…