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Comparative Regression Discontinuity: A Stress Test With Small Samples.
Evaluation Review ( IF 2.121 ) Pub Date : 2018-02-01 , DOI: 10.1177/0193841x18776881
Yasemin Kisbu-Sakarya 1 , Thomas D Cook 2, 3 , Yang Tang 2 , M H Clark 4
Affiliation  

Compared to the randomized experiment (RE), the regression discontinuity design (RDD) has three main limitations: (1) In expectation, its results are unbiased only at the treatment cutoff and not for the entire study population; (2) it is less efficient than the RE and so requires more cases for the same statistical power; and (3) it requires correctly specifying the functional form that relates the assignment and outcome variables. One way to overcome these limitations might be to add a no-treatment functional form to the basic RDD and including it in the outcome analysis as a comparison function rather than as a covariate to increase power. Doing this creates a comparative regression discontinuity design (CRD). It has three untreated regression lines. Two are in the untreated segment of the RDD—the usual RDD one and the added untreated comparison function—while the third is in the treated RDD segment. Also observed is the treated regression line in the treated segment. Recent studies comparing RE, RDD, and CRD causal estimates have found that CRD reduces imprecision compared to RDD and also produces valid causal estimates at the treatment cutoff and also along all the rest of the assignment variable. The present study seeks to replicate these results, but with considerably smaller sample sizes. The power difference between RDD and CRD is replicated, but not the bias results either at the treatment cutoff or away from it. We conclude that CRD without large samples can be dangerous.

中文翻译:

比较回归间断性:小样本压力测试。

与随机实验(RE)相比,回归间断设计(RDD)具有三个主要局限性:(1)预期的是,其结果仅在治疗终止时没有偏倚,而对整个研究人群均无偏见;(2)它的效率不及RE,因此在相同的统计功效下需要更多的案例;(3)要求正确指定与赋值和结果变量相关的功能形式。克服这些局限性的一种方法可能是在基本RDD上添加一个无需处理的功能形式,并将其作为结果比较功能而不是作为协方变量以包括在功效分析中,以增加功效。这样做会创建比较回归不连续性设计(CRD)。它具有三个未处理的回归线。RDD的未处理部分中有两个-常规的RDD一个,还有未处理的比较功能-第三个是RDD的处理中的部分。还观察到在治疗段中的治疗回归线。近期比较RE,RDD和CRD因果估计的研究发现,与RDD相比,CRD降低了不准确性,并且在治疗终止时以及所有其他赋值变量中也产生了有效的因果估计。本研究试图复制这些结果,但样本量要小得多。RDD和CRD之间的功率差被复制,但在治疗截止时或远离治疗截止时不会产生偏倚。我们得出的结论是,没有大量样品的CRD可能很危险。还观察到在治疗段中的治疗回归线。近期比较RE,RDD和CRD因果估计的研究发现,与RDD相比,CRD降低了不准确性,并且在治疗终止时以及所有其他赋值变量中也产生了有效的因果估计。本研究试图复制这些结果,但样本量要小得多。RDD和CRD之间的功率差被复制,但在治疗截止时或远离治疗截止时不会产生偏倚。我们得出的结论是,没有大量样品的CRD可能很危险。还观察到在治疗段中的治疗回归线。近期比较RE,RDD和CRD因果估计的研究发现,与RDD相比,CRD降低了不准确性,并且在治疗终止时以及所有其他赋值变量中也产生了有效的因果估计。本研究试图复制这些结果,但样本量要小得多。RDD和CRD之间的功率差被复制,但在治疗截止时或远离治疗截止时不会产生偏倚。我们得出的结论是,没有大量样品的CRD可能很危险。本研究试图复制这些结果,但样本量要小得多。RDD和CRD之间的功率差被复制,但在治疗截止时或远离治疗截止时不会产生偏倚。我们得出的结论是,没有大量样品的CRD可能很危险。本研究试图复制这些结果,但样本量要小得多。RDD和CRD之间的功率差被复制,但在治疗截止时或远离治疗截止时不会产生偏倚。我们得出的结论是,没有大量样品的CRD可能很危险。
更新日期:2018-02-01
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