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Direct linkWeiland, Christina; Unterman, Rebecca; Dynarski, Susan; Abenavoli, Rachel; Bloom, Howard; Braga, Breno; Faria, Ann-Marie; Greenberg, Erica H.; Jacob, Brian; Arnold Lincove, Jane; Manship, Karen; McCormick, Meghan; Miratrix, Luke; Monarrez, Tomás E.; Morris-Perez, Pamela; Shapiro, Anna; Valant, Jon; Weixler, Lindsay – National Bureau of Economic Research, 2023
Lottery-based identification strategies offer potential for generating the next generation of evidence on U.S. early education programs. Our collaborative network of five research teams applying this design in early education and methods experts has identified six challenges that need to be carefully considered in this next context: (1) available…
Descriptors: Early Childhood Education, Program Evaluation, Evaluation Methods, Admission (School)
Peer reviewedBloom, Howard; Bell, Andrew; Reiman, Kayla – Journal of Research on Educational Effectiveness, 2020
This article assesses the likely generalizability of educational treatment-effect estimates from regression discontinuity designs (RDDs) when treatment assignment is based on academic pretest scores. Our assessment uses data on outcome and pretest measures from six educational experiments, ranging from preschool through high school, to estimate…
Descriptors: Data Use, Randomized Controlled Trials, Research Design, Regression (Statistics)
Download full textBloom, Howard; Bell, Andrew; Reiman, Kayla – Grantee Submission, 2020
This article assesses the likely generalizability of educational treatment-effect estimates from regression discontinuity designs (RDDs) when treatment assignment is based on academic pretest scores. Our assessment uses data on outcome and pretest measures from six educational experiments, ranging from preschool through high school, to estimate…
Descriptors: Data Use, Randomized Controlled Trials, Research Design, Regression (Statistics)
Zhu, Pei; Jacob, Robin; Bloom, Howard; Xu, Zeyu – MDRC, 2011
This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…
Descriptors: Intervention, Academic Achievement, Research Methodology, Research Design
Zhu, Pei; Jacob, Robin; Bloom, Howard; Xu, Zeyu – Educational Evaluation and Policy Analysis, 2012
This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…
Descriptors: Educational Research, Educational Researchers, Research Methodology, Multivariate Analysis
Jacob, Robin; Zhu, Pei; Somers, Marie-Andrée; Bloom, Howard – MDRC, 2012
Regression discontinuity (RD) analysis is a rigorous nonexperimental approach that can be used to estimate program impacts in situations in which candidates are selected for treatment based on whether their value for a numeric rating exceeds a designated threshold or cut-point. Over the last two decades, the regression discontinuity approach has…
Descriptors: Regression (Statistics), Research Design, Graphs, Computation
Jacob, Robin; Zhu, Pei; Bloom, Howard – Journal of Research on Educational Effectiveness, 2010
This article provides practical guidance for researchers who are designing studies that randomize groups to measure the impacts of educational interventions. The article (a) provides new empirical information about the values of parameters that influence the precision of impact estimates (intraclass correlations and R[superscript 2] values) and…
Descriptors: Research Design, Research Methodology, Educational Research, Intervention
Reardon, Sean; Unlu, Fatih; Zhu, Pei; Bloom, Howard – Society for Research on Educational Effectiveness, 2011
The proposed paper studies the bias in the two-stage least squares, or 2SLS, estimator that is caused by the compliance-effect covariance (hereafter, the compliance-effect bias). It starts by deriving the formula for the bias in an infinite sample (i.e., in the absence of finite sample bias) under different circumstances. Specifically, it…
Descriptors: Least Squares Statistics, Bias, Compliance (Psychology), Context Effect
Somers, Marie-Andrée; Zhu, Pei; Jacob, Robin; Bloom, Howard – MDRC, 2013
In this paper, we examine the validity and precision of two nonexperimental study designs (NXDs) that can be used in educational evaluation: the comparative interrupted time series (CITS) design and the difference-in-difference (DD) design. In a CITS design, program impacts are evaluated by looking at whether the treatment group deviates from its…
Descriptors: Research Design, Educational Assessment, Time, Intervals
Bloom, Howard; Zhu, Pei; Jacob, Robin; Raudenbush, Stephen; Martinez, Andres; Lin, Fen – MDRC, 2008
This paper provides practical guidance for researchers who are designing studies that randomize groups to measure the impacts of interventions on children. To do so, the paper: (1) provides new empirical information about the values of parameters that influence the precision of impact estimates (intra-class correlations and R-squares); (2)…
Descriptors: Pilot Projects, Research Methodology, Intervention, Sampling
