| 来源类型 | Publication |
| 来源ID | Working Paper 21 |
| Replicating Experimental Impact Estimates with Nonexperimental Methods in the Context of Control Crossover | |
| Brian Gill; Joshua Furgeson; Hanley S. Chiang; Bing-Ru Teh; Joshua Haimson; and Natalya Verbitsky-Savitz | |
| 发表日期 | 2013-10-30 |
| 出版者 | Cambridge, MA: Mathematica Policy Research |
| 出版年 | 2013 |
| 语种 | 英语 |
| 概述 | Ideally, nonexperimental methods that aim to replicate the results of rigorous randomized experiments focus on the intent to treat (ITT) experimental impact estimate, the most causally rigorous measure.", |
| 摘要 | Ideally, nonexperimental methods that aim to replicate the results of rigorous randomized experiments focus on the intent to treat (ITT) experimental impact estimate, the most causally rigorous measure. This working paper develops a new replication approach that facilitates testing nonexperimental methods against rigorous experimental ITT impact estimates when the experiment includes substantial control crossover. |
| URL | https://www.mathematica.org/our-publications-and-findings/publications/replicating-experimental-impact-estimates-with-nonexperimental-methods-in-the-context-of-control-crossover |
| 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/487532 |
| 推荐引用方式 GB/T 7714 | Brian Gill,Joshua Furgeson,Hanley S. Chiang,et al. Replicating Experimental Impact Estimates with Nonexperimental Methods in the Context of Control Crossover. 2013. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| crossover_replicatio（325KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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