Showing 81 - 90 of 153
Finds that, a year or more after enrolling in the program, 2-year-olds perform significantly better on a range of measures of cognitive, language, and social-emotional development, when compared with a randomly assigned control group. EHS families are also more likely to attend school or job...
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Pretest and post-test experimental designs are often used in randomized control trials (RCTs) in the education field to improve the precision of the estimated treatment effects. For logistic reasons, however, pretest data are often collected after random assignment, so that including them in the...
Persistent link: https://www.econbiz.de/10010608737
This article examines theoretical and empirical issues related to the statistical power of impact estimates for experimental evaluations of education programs. The author considers designs where random assignment is conducted at the school, classroom, or student level, and employs a unified...
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For randomized controlled trials (RCTs) of education interventions, estimates of associations between student and mediating teacher practice outcomes can help examine the extent to which the data support the study's conceptual model. They can also identify mediators most associated with student...
Persistent link: https://www.econbiz.de/10010609003
This paper examines the estimation of two-stage clustered randomized controlled trial designs (RCTs) in education research using the Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control...
Persistent link: https://www.econbiz.de/10010609010
This paper examines theoretical and empirical issues related to the statistical power of impact estimates for experimental evaluations of education programs. It considers designs in which random assignment is conducted at the school, classroom, or student level, using a unified analytic...
Persistent link: https://www.econbiz.de/10010609067
In social policy evaluations, the multiple testing problem occurs due to the many hypothesis tests typically conducted across multiple outcomes and subgroups, which can lead to spurious impact findings. This article discusses a framework that balances Types I and II errors for addressing this...
Persistent link: https://www.econbiz.de/10010609129