| 来源类型 | Publication |
| Design-Based Estimators for Average Treatment Effects for Multi-Armed RCTs | |
| Peter Z. Schochet | |
| 发表日期 | 2018-10-01 |
| 出版者 | Journal of Educational and Behavioral Statistics, vol. 43, issue 5 (subscription required) |
| 出版年 | 2018 |
| 语种 | 英语 |
| 概述 | This article builds on this framework to develop design-based estimators for evaluations with multiple research groups.", |
| 摘要 | Design-based methods have recently been developed as a way to analyze randomized controlled trial (RCT) data for designs with a single treatment and control group. This article builds on this framework to develop design-based estimators for evaluations with multiple research groups. Results are provided for a wide range of designs used in education research, including clustered and blocked designs. Because analysis in the multi-armed setting involves pairwise contrasts across the research groups, the key methodological question addressed is: How do the estimators for the two-group design need to be adjusted for multi-armed trials? The critical insight is that in multi-armed trials where the goal is to identify the most effective treatments, the samples for each pairwise contrast are representative of the full set of randomized units, not just of themselves. The implication is that variance terms need to be adjusted slightly under the finite-population framework that can reduce precision, and blocks need to be weighted to reflect the full randomized sample in the block or biases can result. An empirical example using data from a multi-armed education RCT demonstrates the issues. |
| URL | https://www.mathematica.org/our-publications-and-findings/publications/design-based-estimators-for-average-treatment-effects-for-multi-armed-rcts |
| 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/489371 |
| 推荐引用方式 GB/T 7714 | Peter Z. Schochet. Design-Based Estimators for Average Treatment Effects for Multi-Armed RCTs. 2018. |
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