摘要翻译：
在客户忠诚度计划和奖学金计划的激励下，我们研究了随机对照试验(RCTs)和回归间断设计(RDDs)的混合设计。我们量化了一个平衡点设计的统计效率，在这个设计中，有一个比例$\\δ$的观察对象在RCT中。在两行回归中，统计效率随$\delta单调增加，因此效率通过RCT最大化。我们指出了与RDD相比的附加优势：对于非参数回归，边界偏差要小得多，对于二次回归，方差大大减小。对于两行模型，我们可以量化治疗分配的短期值，这种比较有利于更小的$\delta$，RDD是最好的。我们解决了这些勘探和开发目标之间的最优权衡。通常的打分设计将RCT应用于按赋值变量排序的中间$\delta$主题。我们量化了其他设计的效率，例如只在从顶部开始的第二个十进制进行实验。我们还证明了在一些一般的参数模型中，蒙特卡罗计算可以用矩阵代数来代替。
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英文标题：
《Optimizing the tie-breaker regression discontinuity design》
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作者：
Art B. Owen and Hal Varian
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最新提交年份：
2020
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  Motivated by customer loyalty plans and scholarship programs, we study tie-breaker designs which are hybrids of randomized controlled trials (RCTs) and regression discontinuity designs (RDDs). We quantify the statistical efficiency of a tie-breaker design in which a proportion $\Delta$ of observed subjects are in the RCT. In a two line regression, statistical efficiency increases monotonically with $\Delta$, so efficiency is maximized by an RCT. We point to additional advantages of tie-breakers versus RDD: for a nonparametric regression the boundary bias is much less severe and for quadratic regression, the variance is greatly reduced. For a two line model we can quantify the short term value of the treatment allocation and this comparison favors smaller $\Delta$ with the RDD being best. We solve for the optimal tradeoff between these exploration and exploitation goals. The usual tie-breaker design applies an RCT on the middle $\Delta$ subjects as ranked by the assignment variable. We quantify the efficiency of other designs such as experimenting only in the second decile from the top. We also show that in some general parametric models a Monte Carlo evaluation can be replaced by matrix algebra.
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PDF链接：
https://arxiv.org/pdf/1808.07563