Regression Discontinuity Designs With Multiple Rating-Score Variables

被引:87
作者
Reardon, Sean F. [1 ]
Robinson, Joseph P. [2 ]
机构
[1] Stanford Univ, Stanford, CA 94305 USA
[2] Univ Illinois, Champaign, IL USA
关键词
causal inference; regression discontinuity design; multiple rating score variables; STATISTICS; IDENTIFICATION; ACHIEVEMENT; INFERENCE; EDUCATION; SCHOOL; LIFE;
D O I
10.1080/19345747.2011.609583
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
In the absence of a randomized control trial, regression discontinuity (RD) designs can produce plausible estimates of the treatment effect on an outcome for individuals near a cutoff score. In the standard RD design, individuals with rating scores higher than some exogenously determined cutoff score are assigned to one treatment condition; those with rating scores below the cutoff score are assigned to an alternate treatment condition. Many education policies, however, assign treatment status on the basis of more than one rating-score dimension. We refer to this class of RD designs as "multiple rating score regression discontinuity" (MRSRD) designs. In this paper, we discuss five different approaches to estimating treatment effects using MRSRD designs (response surface RD; frontier RD; fuzzy frontier RD; distance-based RD; and binding-score RD). We discuss differences among them in terms of their estimands, applications, statistical power, and potential extensions for studying heterogeneity of treatment effects.
引用
收藏
页码:83 / 104
页数:22
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