This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses.
This study sought to determine the impact of Healthy Families Healthy Futures (HFHF) enhanced with Steps to Success (STS).
This article uses an evaluation of New Heights, a school-based program for pregnant and parenting teens in the District of Columbia Public Schools, to illustrate how maternal and child health programs can obtain rigorous evaluations at reasonable cost using extant administrative data.
Helping principals improve their leadership practices is a common use of federal funds and one way to improve instruction and student achievement.
The Institute of Education Sciences conducted a random assignment study of an intensive professional development program for elementary school principals.
This brief describes an alternative framework for interpreting impact estimates, known as the BAyeSian Interpretation of Estimates (BASIE).
Federally funded systematic reviews of research evidence play a central role in efforts to base policy decisions on evidence.
The authors examine the potential for small biases to increase the risk of making false inferences as studies are powered to detect smaller impacts and recommend strategies researchers can use to avoid or mitigate these biases.
This brief summarizes the impacts of New Heights, a program that serves expectant and parenting teens, in Washington D.C. public schools (DCPS). The program is being evaluated as part of the Positive Adolescent Futures study, funded by the Office of Adolescent Health (OAH).
Systematic reviews that assess the quality of research on program effectiveness can help decision makers faced with many intervention options.
This report shares the findings from an impact and implementation study of New Heights, a DC Public Schools program that provides a multi-faceted approach for supporting parenting students’ educational attainment.
The purpose of this article is to explain the WWC attrition model, how that model is used to establish attrition bounds, and to assess the sensitivity of attrition bounds to key parameter values.
This brief summarizes findings from a new report from Mathematica’s multiyear evaluation of School Improvement Grants (SIG) for the Department of Education’s Institute of Education Sciences. It describes the practices schools used and examines the impact of SIG on student achievement.
This executive summary describes key findings from a report from Mathematica’s multiyear evaluation of School Improvement Grants (SIG) for the Department of Education’s Institute of Education Sciences. It describes the practices schools used and examines the impact of SIG on student achievement.
This report summarizes findings from Mathematica’s multiyear evaluation of School Improvement Grants (SIG) for the Department of Education’s Institute of Education Sciences. It describes the practices schools used and examines the impact of SIG on student achievement.
This report summarizes findings from Mathematica’s multiyear evaluation of Race to the Top (RTT) for the Department of Education’s Institute of Education Sciences.
This brief summarizes findings from a new report from Mathematica’s multiyear evaluation of Race to the Top (RTT) for the Department of Education’s Institute of Education Sciences.
This executive summary describes key findings from a report from Mathematica’s multiyear evaluation of Race to the Top (RTT) for the Department of Education’s Institute of Education Sciences.
Cluster randomized controlled trials (CRCTs) often require a large number of clusters in order to detect small effects with high probability.
This report examines the Home Visiting Evidence of Effectiveness Review's attrition standard and how its boundary responds to changes in two fundamental assumptions: (1) the correlation between outcomes and attrition, and (2) the level of attrition bias deemed acceptable.
In this brief we examine methodological criticisms of the Linear Probability Model (LPM) in general and conclude that these criticisms are not relevant to experimental impact analysis.
Variation in treatment effects has important implications for education practice—and for facilitating the most efficient use of limited resources—by informing decisions about how best to target interventions and how to improve the design or implementation of interventions.
One of the modifications of the Elementary and Secondary Education Act (known as the No Child Left Behind Act) gave parents of low-income students in low-performing schools a choice of Supplemental Educational Services (SEdS).
This update answers frequently asked questions about the implications of clustering in clustered randomized controlled trials (RCTs).
In this brief we describe strategies for coping with missing data in RCTs.
This update features answers to frequently asked questions about starting an effectiveness evaluation, such as gathering consent and collecting baseline data.
This paper compares the precision gains from adjusting impact estimates for student-level pretest scores (which can be costly to collect) with the gains associated with using publically available school-level proficiency data (available at low cost), using data from five large-scale randomized control...
This report presents findings from an evaluation of the mandatory-random student drug testing (MRSDT) programs in 36 high schools from seven districts that received grants from the U.S. Department of Education’s Office of Safe and Drug-Free Schools in 2006.
This study evaluated the effectiveness of four supplemental reading comprehension programs in helping disadvantaged fifth graders improve reading comprehension.