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Research Methodology |
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Empirical Issues in the Design of Group-Randomized Studies to Measure the Effects of Interventions for Children
Working Paper
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2008. Howard Bloom, Pei Zhu, Robin Jacob, Stephen Raudenbush, Andres Martinez, and Fen Lin.
This MDRC working paper on research methodology provides practical guidance for researchers who are designing studies that randomize groups to measure the impacts of interventions on children.
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Empirical Benchmarks for Interpreting Effect Sizes in Research
Working Paper
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2007. Carolyn J. Hill, Howard S. Bloom, Alison Rebeck Black, and Mark W. Lipsey.
No universal guideline exists for judging the practical importance of a standardized effect size, a measure of the magnitude of an intervention's effects. This working paper argues that effect sizes should be interpreted using empirical benchmarks — and presents three types in the context of education research.
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The Core Analytics of Randomized Experiments for Social Research
Working Paper
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2006. Howard S. Bloom.
This MDRC research methodology working paper examines the core analytic elements of randomized experiments for social research. Its goal is to provide a compact discussion of the design and analysis of randomized experiments for measuring the impact of social or educational interventions.
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Making Random Assignment Happen
Evidence from the UK Employment Retention and Advancement (ERA) Demonstration
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UK Department for Work and Pensions.
2006. Robert Walker, Lesley Hoggart, and Gayle Hamilton, with Susan Blank.
The largest ever random assignment test of a social policy in Britain is being applied in a demonstration of the Employment Retention and Advancement (ERA) program. This report, written by MDRC and British colleagues as part of a consortium of social policy research firms and produced for the UK Department for Work and Pensions, examines how well random assignment worked.
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Using Covariates to Improve Precision
Empirical Guidance for Studies That Randomize Schools to Measure the Impacts of Educational Interventions
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2005. Howard S. Bloom, Lashawn Richburg-Hayes, and Alison Rebeck Black.
This paper examines how controlling statistically for baseline covariates (especially pretests) improves the precision of studies that randomize schools to measure the impacts of educational interventions on student achievement.
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Conducting Classroom Observations in First Things First Schools
Working Paper
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2004. Angela Estacion, Teresa McMahon, Janet Quint, with Bernice Melamud and LaFleur Stephens.
Relying on 427 classroom observations conducted over a three-year period, this study traces changes in teachers’ instructional practices in the First Things First schools.
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Sample Design for an Evaluation of the Reading First Program
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2003. Howard S. Bloom.
This paper illustrates how to design an experimental sample for measuring the effects of educational programs when whole schools are randomized to a program and control group. It addresses such issues as what number of schools should be randomized, how many students per school are needed, and what is the best mix of program and control schools.
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Exploring the Feasibility and Quality of Matched Neighborhood Research Designs
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2003. David C. Seith, Nandita Verma, Howard S. Bloom, George C. Galster.
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Intensive Qualitative Research
Challenges, Best Uses, and Opportunities
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2003. Alissa Gardenhire and Laura Nelson.
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"Help, I'm Getting Buried in Field Notes!"
A Manual for Qualitative Data Management and Analysis
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2003. Rebecca Widom with Herbert Collado.
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Using Instrumental Variables Analysis to Learn More from Social Policy Experiments
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2002. Lisa A. Gennetian, Johannes M. Bos, Pamela A. Morris.
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Using Place-Based Random Assignment and Comparative Interrupted Time-Series Analysis to Evaluate the Jobs-Plus Employment Program for Public Housing Residents
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2002. Howard S. Bloom, James A. Riccio.
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Can Nonexperimental Comparison Group Methods Match the Findings from a Random Assignment Evaluation of Mandatory Welfare-to-Work Programs?
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2002. Howard S. Bloom, Charles Michalopoulos, Carolyn J. Hill, Ying Lei.
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Measuring the Impacts of Whole-School Reforms
Methodological Lessons from an Evaluation of Accelerated Schools
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2001. Howard S. Bloom.
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Extending the Reach of Randomized Social Experiments
New Directions in Evaluations of American Welfare-to-Work and Employment Initiatives
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2001. James A Riccio, Howard S. Bloom.
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A Meta-Analysis of Government Sponsored Training Programs
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University of Maryland Baltimore County.
2001. David H. Greenberg, Charles Michalopoulos, Philip K. Robins.
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Modeling the Performance of Welfare-to-Work Programs
The Effects of Program Management and Services, Economic Environment, and Client Characteristics
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2001. Howard S. Bloom, Carolyn J. Hill, James Riccio.
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A Regression-Based Strategy for Defining Subgroups in a Social Experiment
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2001. James J. Kemple, Jason C. Snipes with Howard Bloom.
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Assessing the Impact of Welfare Reform on Urban Communities
The Urban Change Project and Methodological Considerations
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2000. Charles Michalopoulos, Johannes M. Bos, Robert Lalonde, Nandita Verma.
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The Politics of Random Assignment
Implementing Studies and Impacting Policy
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2000. Judith M. Gueron.
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Building a Convincing Test of a Public Housing Employment Program Using Non-Experimental Methods
Planning for the Jobs-Plus Demonstration
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1999. Howard Bloom.
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Estimating Program Impacts on Student Achievement Using "Short" Interrupted Time Series
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1999. Howard S. Bloom.
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Using Cluster Random Assignment to Measure Program Impacts
Statistical Implications for the Evaluation of Education Programs
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1999. Howard S. Bloom, Johannes M. Bos, Suk-Won Lee.
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