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Ben Weidmann's "Missing, presumed different: Quantifying the risk of attrition bias in education evaluations" published by Royal Statistical Society

March 10, 2021
In this paper, soon-to-be-Doctor Weidmann used an administrative database to assess the magnitude of attrition bias in a collection of education randomized trials. There was not much to be found. Weidmann then extended this work, proposing a simple sensitivity analysis one might use on any trial of one's own or even read about to gauge how much attrition may have played a role in a found impact or lack thereof. To view, please click here. Read more about Ben Weidmann's "Missing, presumed different: Quantifying the risk of attrition bias in education evaluations" published by Royal Statistical Society

Sophie Litschwartz wins AERA/NSF grant for her project "Characterizing Cross-Site Variation in Local Average Treatment Effects in Multisite RDD Contexts with an Application to High School Math Graduation Requirements"

February 1, 2021

We are happy to announce that Sophie Litschwartz was awarded an AERA/NSF Dissertation and Research Grant for her project titled “Characterizing Cross-Site Variation in Local Average Treatment Effects in Multisite RDD Contexts with an Application to High School Math Graduation Requirements.” Congratulations, Sophie! For more information, please click...

Read more about Sophie Litschwartz wins AERA/NSF grant for her project "Characterizing Cross-Site Variation in Local Average Treatment Effects in Multisite RDD Contexts with an Application to High School Math Graduation Requirements"

Weidmann & Miratrix publish "Lurking inferential monsters? Quantifying selection bias in evaluations of school programs"

December 14, 2020

Ben Weidmann and Luke Miratrix have published "Lurking inferential monsters? Quantifying selection bias in evaluations of school programs." Ben has made some great strides in understanding how well we might use matching to conduct observational studies on national student datasets for interventions taken up at the school level. In this work, he conducts a within study...

Read more about Weidmann & Miratrix publish "Lurking inferential monsters? Quantifying selection bias in evaluations of school programs"

IES Grant Awarded to Luke Miratrix for project "Improving Methods for Policy Impact Evaluation with Group Panel Data in Education Research"

June 26, 2020
Luke Miratrix, along with co-PIs Avi Feller and Jesse Rothstein, have been awarded a three year Institute of Education Sciences grant for their project titled "Improving Methods for Policy Impact Evaluation with Group Panel Data in Education Research". This is incredibly exciting news for everyone at the CARES lab! Check out the details of the award here. Read more about IES Grant Awarded to Luke Miratrix for project "Improving Methods for Policy Impact Evaluation with Group Panel Data in Education Research"

Quinn joins the MIT Probabilistic Computing Project

May 6, 2020
Recent PhD graduate Jameson Quinn has joined the exciting MIT Probabilistic Computing Project on Gen.jl, a latest-generation probabilistic programming language. Jameson's work so far has focused on building teaching examples of the process of engineering and testing MCMC and/or SMC sampling schemes, with applications to COVID-19 models. We look forward to see what comes next of the project, and Jameson's work in particular! Read more about Quinn joins the MIT Probabilistic Computing Project

Pashley appointed Assistant Professor at Rutgers

May 6, 2020

Please join us in congratulating Nicole Pashley, who has been appointed as an Assistant Professor in Rutgers University’s Department of Statistics beginning next academic year. We look forward to seeing what comes next in Nicole's career!