Randomization-based confidence sets for the local average treatment effect
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910819466346496 |
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| author | Aronow, P. M. Chang, Haoge Lopatto, Patrick |
| author_facet | Aronow, P. M. Chang, Haoge Lopatto, Patrick |
| contents | We consider the problem of generating confidence sets in randomized experiments with noncompliance. We show that a refinement of a randomization-based procedure proposed by Imbens and Rosenbaum (2005) has desirable properties. Namely, we show that using a studentized Anderson--Rubin-type statistic as a test statistic yields confidence sets that are finite-sample exact under treatment effect homogeneity, and remain asymptotically valid for the Local Average Treatment Effect when the treatment effect is heterogeneous. We provide a uniform analysis of this procedure and efficient algorithms to construct the confidence set. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2404_18786 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Randomization-based confidence sets for the local average treatment effect Aronow, P. M. Chang, Haoge Lopatto, Patrick Statistics Theory Methodology We consider the problem of generating confidence sets in randomized experiments with noncompliance. We show that a refinement of a randomization-based procedure proposed by Imbens and Rosenbaum (2005) has desirable properties. Namely, we show that using a studentized Anderson--Rubin-type statistic as a test statistic yields confidence sets that are finite-sample exact under treatment effect homogeneity, and remain asymptotically valid for the Local Average Treatment Effect when the treatment effect is heterogeneous. We provide a uniform analysis of this procedure and efficient algorithms to construct the confidence set. |
| title | Randomization-based confidence sets for the local average treatment effect |
| topic | Statistics Theory Methodology |
| url | https://arxiv.org/abs/2404.18786 |