Department of Biostatistics, University of Washington, Seattle, Washington, USA.
Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York, USA.
Biometrics. 2023 Jun;79(2):601-603. doi: 10.1111/biom.13780. Epub 2022 Oct 31.
We thank all the discussants for the careful reading and insightful comments. In our rejoinder, we extend the discussion of how the assumptions of instrumented difference-in-differences (iDID) compare to the assumptions of the standard instrumental variable method. We also make additional comments on how iDID is related to the fuzzy DID. We highlight future research directions to enhance the utility of iDID, including extensions to adjust for covariate shift in two-sample iDID design, and generalization of iDID to multiple time points and a multi-valued instrumental variable for DID.
我们感谢所有讨论者的仔细阅读和深入评论。在我们的回应中，我们进一步讨论了工具差分（iDID）的假设与标准工具变量方法的假设相比有何不同。我们还就 iDID 与模糊 DID 的关系发表了更多评论。我们强调了增强 iDID 实用性的未来研究方向，包括扩展两样本 iDID 设计中协变量偏移的调整，以及将 iDID 推广到多个时间点和多值工具变量用于 DID。
