Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Intervention | 2 |
| Monte Carlo Methods | 2 |
| Randomized Controlled Trials | 2 |
| Regression (Statistics) | 2 |
| Research Design | 2 |
| Research Problems | 2 |
| Statistical Bias | 2 |
| Attrition (Research Studies) | 1 |
| Comparative Analysis | 1 |
| Control Groups | 1 |
| Economics | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 2 |
| Numerical/Quantitative Data | 1 |
Education Level
| Elementary Education | 1 |
| Grade 4 | 1 |
| Intermediate Grades | 1 |
Audience
Location
| Cambodia | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textDeke, John; Wei, Thomas; Kautz, Tim – National Center for Education Evaluation and Regional Assistance, 2017
Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…
Descriptors: Intervention, Educational Research, Research Problems, Statistical Bias
Barrera-Osorio, Felipe; Filmer, Deon; McIntyre, Joe – Society for Research on Educational Effectiveness, 2014
Randomized controlled trials (RCTs) and regression discontinuity (RD) studies both provide estimates of causal effects. A major difference between the two is that RD only estimates local average treatment effects (LATE) near the cutoff point of the forcing variable. This has been cited as a drawback to RD designs (Cook & Wong, 2008).…
Descriptors: Randomized Controlled Trials, Regression (Statistics), Research Problems, Comparative Analysis
