NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
PDF on ERIC Download full text
ERIC Number: ED556496
Record Type: Non-Journal
Publication Date: 2015-May
Pages: 154
Abstractor: As Provided
Reference Count: 83
Statistical Theory for the "RCT-YES" Software: Design-Based Causal Inference for RCTs. NCEE 2015-4011
Schochet, Peter Z.
National Center for Education Evaluation and Regional Assistance
This report presents the statistical theory underlying the "RCT-YES" software that estimates and reports impacts for RCTs for a wide range of designs used in social policy research. The report discusses a unified, non-parametric design-based approach for impact estimation using the building blocks of the Neyman-Rubin-Holland causal inference model that underlies experimental designs. This approach differs from the more model-based impact estimation methods that are typically used in education research. The report discusses impact and variance estimation, asymptotic distributions of the estimators, hypothesis testing, the inclusion of baseline covariates to improve precision, the use of weights, subgroup analyses, baseline equivalency analyses, and estimation of the complier average causal effect parameter. A section on mathematical proofs is appended.
National Center for Education Evaluation and Regional Assistance. Available from: ED Pubs. P.O. Box 1398, Jessup, MD 20794-1398. Tel: 877-433-7827; Web site:
Publication Type: Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: National Center for Education Evaluation and Regional Assistance (ED); Decision Information Resources, Inc.
IES Funded: Yes
Grant or Contract Numbers: ED-IES-12-C-0057