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来源类型 | Publication |
Replicating Experimental Impact Estimates With Nonexperimental Methods in the Context of Control-Group Noncompliance | |
Brian Gill; Joshua Furgeson; Hanley Chiang; Bing-Ru Teh; Joshua Haimson; and Natalya Verbitsky-Savitz | |
发表日期 | 2015-12-14 |
出版者 | Statistics and Public Policy (published online ahead of print, subscription required) |
出版年 | 2015 |
语种 | 英语 |
概述 | A growing literature on within-study comparisons (WSC) examines whether and in what context nonexperimental methods can successfully replicate the results of randomized experiments.", |
摘要 | A growing literature on within-study comparisons (WSC) examines whether and in what context nonexperimental methods can successfully replicate the results of randomized experiments. WSCs require that the experimental and nonexperimental methods assess the same causal estimand (Cook, Shadish, and Wong, 2008). But experiments that include noncompliance in treatment assignment produce a divergence in the causal estimands measured by standard approaches: the experiment-based estimate of the impact of treatment (the complier average causal effect, CACE) applies only to compliers, while the non-experimental estimate applies to all subjects receiving treatment, including always-takers.
We develop a new replication approach that solves this problem by using nonexperimental methods to produce an estimate that can be compared to the experimental intent-to-treat (ITT) impact estimate rather than the CACE. We demonstrate the applicability of the method in a WSC of the effects of charter schools on student achievement. In our example, some members of the randomized control group crossed over to treatment by enrolling in the charter schools. We show that several nonexperimental methods that incorporate pre-treatment measures of the outcome of interest can successfully replicate experimental ITT impact estimates when control-group noncompliance (crossover) occurs—even when treatment effects differ for compliers and always takers. |
URL | https://www.mathematica.org/our-publications-and-findings/publications/2015-replicating-experimental-impact-estimates-with-nonexperimental-methods-in-the-context |
来源智库 | Mathematica Policy Research (United States) |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/488361 |
推荐引用方式 GB/T 7714 | Brian Gill,Joshua Furgeson,Hanley Chiang,et al. Replicating Experimental Impact Estimates With Nonexperimental Methods in the Context of Control-Group Noncompliance. 2015. |
条目包含的文件 | 条目无相关文件。 |
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