论文标题
小型研究回归不连续性设计：密度包容性研究尺寸指标和性能
Small Study Regression Discontinuity Designs: Density Inclusive Study Size Metric and Performance
论文作者
论文摘要
回归不连续性（RD）设计是流行的准实验研究，其中治疗分配取决于运行变量的值是否超过截止。由于基于截止的干预措施的流行，RD设计在教育应用中越来越流行。在此类应用中，样本量可能相对较小，也可能周围可能存在稀疏性。我们提出了一个度量，密度包含研究的尺寸（DISS），通过结合运行变量的密度，它比整体样本量更好地表征了RD研究的大小。我们在蒙特卡洛模拟研究中显示了该指标的有用性，该研究比较了小型研究中流行的非参数RD估计方法的工作特征。我们还将DISS指标和RD估计方法应用于印第安纳州的学校问责制数据。
Regression discontinuity (RD) designs are popular quasi-experimental studies in which treatment assignment depends on whether the value of a running variable exceeds a cutoff. RD designs are increasingly popular in educational applications due to the prevalence of cutoff-based interventions. In such applications sample sizes can be relatively small or there may be sparsity around the cutoff. We propose a metric, density inclusive study size (DISS), that characterizes the size of an RD study better than overall sample size by incorporating the density of the running variable. We show the usefulness of this metric in a Monte Carlo simulation study that compares the operating characteristics of popular nonparametric RD estimation methods in small studies. We also apply the DISS metric and RD estimation methods to school accountability data from the state of Indiana.
