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ERIC Number: ED556496
Record Type: Non-Journal
Publication Date: 2015-May
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.
Descriptors: Statistics, Computer Software, Inferences, Research Design, Educational Research, Nonparametric Statistics, Computation, Hypothesis Testing, Mathematical Logic, Validity, Simulation, Outcome Measures
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: http://ies.ed.gov/ncee/
Publication Type: Reports - Research
Education Level: 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
IES Publication: http://ies.ed.gov/pubsearch/pubsinfo.asp?pubid=NCEE20154011