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About IES

Howard Bloom

Ph.D.
Chief Social Scientist
MDRC

About

Howard Bloom is a chief social scientist at MDRC. Dr. Bloom leads the development of experimental and quasi-experimental methods for estimating program impacts initiative, working closely with MDRC staff to build these methods into their research. He came to MDRC in 1999, following 21 years of teaching research methods, program evaluation, and applied statistics at Harvard University and at New York University, where he received the Great Teacher Award in 1993. The author of numerous articles and several books, Dr. Bloom has been a principal investigator of four major randomized experiments: the National Job Training Partnership Act study, a 20,000-person evaluation conducted in 16 U.S. cities; the Earnings Supplement Project, an 8,000-person study conducted in five Canadian cities; the Texas Displaced Worker Study; and the Delaware Displaced Worker Study. Having earned his bachelor's degree in engineering from Case Western Reserve University, Dr. Bloom holds a Master of City Planning, a Master of Public Administration, and a Ph.D. in political economy and government from Harvard University.

Associated IES Content

FY2012

Single-Session Panels

Minutes of Meeting: November 1, 2010

NBES meeting minutes on November 1, 2010
Grant

An Empirical Analysis of Two Methodological Issues for Education Research Caused by Variation in Program Impacts

The purpose of the project is to investigate two issues pertinent to the variation in treatment effects across sites in a multisite trial. The first issue is the impact of cross-site variation on a study's statistical power to detect the mean treatment effect across all sites.
Federal funding program:
Statistical and Research Methodology in Education
Award number:
R305D140012
Grant

Regression Discontinuity Designs with Assignment Based on Multiple Rating Scores: Statistical Properties and Issues in the Context of Education Evaluation

The purpose of this project was to provide practical guidance to education researchers on how to estimate program impacts using a regression discontinuity (RD) design with more than one rating variable. It is often the case that assignment to an education intervention is based on multiple criteria. For example, graduation from high school may depend on a student successfully passing standardized tests in several subjects and meeting Adequate Yearly Progress requires schools to meet a number ...
Federal funding program:
Statistical and Research Methodology in Education
Award number:
R305D100027

FY2011 IES Peer Reviewers

FY2011 IES Research Peer Review Panel
Grant

Using Instrumental Variables Analysis Coupled with Rigorous Multi-Site Impact Studies to Study the Causal Paths by which Educational Interventions Affect Student Outcomes

This project explored the theoretical properties and empirical implications of using instrumental variables analysis coupled with rigorous multi-site impact studies to estimate the causal paths by which educational interventions produce effects on students. To this end, it addressed five research questions:
Federal funding program:
Statistical and Research Methodology in Education
Award number:
R305D090009

FY2010 IES Peer Reviewers

FY2010 IES Research Peer Review Panel
Grant

Statistical Properties of Regression Discontinuity Analysis and Comparative Interrupted Time Series Analysis for Estimating Impacts

This project explored the circumstances under which two promising quasi-experimental designs can produce estimates of program impacts that are valid, precise and generalizable.
Federal funding program:
Statistical and Research Methodology in Education
Award number:
R305D090008
Workshop/Training

2007 IES Research Training Institute: Cluster Randomized Trials

To increase the national capacity to develop and conduct rigorous evaluations of the effectiveness of education interventions by training researchers to conduct cluster (group) randomized trials in education settings.
event
Jun 17, 2007 12:00AM - 11:59PM EDT
organization

MDRC

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