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ERIC Number: EJ1004543
Record Type: Journal
Publication Date: 2013-Apr
Pages: 35
Abstractor: As Provided
ISSN: ISSN-1076-9986
Analyzing Regression-Discontinuity Designs with Multiple Assignment Variables: A Comparative Study of Four Estimation Methods
Wong, Vivian C.; Steiner, Peter M.; Cook, Thomas D.
Journal of Educational and Behavioral Statistics, v38 n2 p107-141 Apr 2013
In a traditional regression-discontinuity design (RDD), units are assigned to treatment on the basis of a cutoff score and a continuous assignment variable. The treatment effect is measured at a single cutoff location along the assignment variable. This article introduces the multivariate regression-discontinuity design (MRDD), where multiple assignment variables and cutoffs may be used for treatment assignment. For an MRDD with two assignment variables, we show that the frontier average treatment effect can be decomposed into a weighted average of two univariate RDD effects. The article discusses four methods for estimating MRDD treatment effects and compares their relative performance in a Monte Carlo simulation study under different scenarios. (Contains 4 tables, 5 figures and 6 notes.)
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
IES Funded: Yes
Grant or Contract Numbers: R305D100033
IES Cited: ED560820