Improving the Estimation of Site-Specific Effects and their Distribution in Multisite Trials
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866911822263615488 |
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| author | Lee, JoonHo Che, Jonathan Rabe-Hesketh, Sophia Feller, Avi Miratrix, Luke |
| author_facet | Lee, JoonHo Che, Jonathan Rabe-Hesketh, Sophia Feller, Avi Miratrix, Luke |
| contents | In multisite trials, researchers are often interested in several inferential goals: estimating treatment effects for each site, ranking these effects, and studying their distribution. This study seeks to identify optimal methods for estimating these targets. Through a comprehensive simulation study, we assess two strategies and their combined effects: semiparametric modeling of the prior distribution, and alternative posterior summary methods tailored to minimize specific loss functions. Our findings highlight that the success of different estimation strategies depends largely on the amount of within-site and between-site information available from the data. We discuss how our results can guide balancing the trade-offs associated with shrinkage in limited data environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_06913 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Improving the Estimation of Site-Specific Effects and their Distribution in Multisite Trials Lee, JoonHo Che, Jonathan Rabe-Hesketh, Sophia Feller, Avi Miratrix, Luke Methodology Applications In multisite trials, researchers are often interested in several inferential goals: estimating treatment effects for each site, ranking these effects, and studying their distribution. This study seeks to identify optimal methods for estimating these targets. Through a comprehensive simulation study, we assess two strategies and their combined effects: semiparametric modeling of the prior distribution, and alternative posterior summary methods tailored to minimize specific loss functions. Our findings highlight that the success of different estimation strategies depends largely on the amount of within-site and between-site information available from the data. We discuss how our results can guide balancing the trade-offs associated with shrinkage in limited data environments. |
| title | Improving the Estimation of Site-Specific Effects and their Distribution in Multisite Trials |
| topic | Methodology Applications |
| url | https://arxiv.org/abs/2308.06913 |