Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 1 |
Descriptor
Algorithms | 1 |
Bayesian Statistics | 1 |
Causal Models | 1 |
Educational Research | 1 |
Error of Measurement | 1 |
Experiments | 1 |
Prediction | 1 |
Randomized Controlled Trials | 1 |
Sample Size | 1 |
Sampling | 1 |
Statistical Bias | 1 |
More ▼ |
Source
Grantee Submission | 1 |
Author
Botelho, A. F. | 1 |
Erickson, J. A. | 1 |
Gagnon-Bartsch, J. A. | 1 |
Heffernan, N. T. | 1 |
Miratrix, L. W. | 1 |
Sales, A. C. | 1 |
Wu, E. | 1 |
Publication Type
Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Gagnon-Bartsch, J. A.; Sales, A. C.; Wu, E.; Botelho, A. F.; Erickson, J. A.; Miratrix, L. W.; Heffernan, N. T. – Grantee Submission, 2019
Randomized controlled trials (RCTs) admit unconfounded design-based inference--randomization largely justifies the assumptions underlying statistical effect estimates--but often have limited sample sizes. However, researchers may have access to big observational data on covariates and outcomes from RCT non-participants. For example, data from A/B…
Descriptors: Randomized Controlled Trials, Educational Research, Prediction, Algorithms