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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.00795 |
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| _version_ | 1866913570269167616 |
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| author | Kulinskaya, Elena Hoaglin, David C. |
| author_facet | Kulinskaya, Elena Hoaglin, David C. |
| contents | We consider a three-level meta-analysis of standardized mean differences. The standard method of estimation uses inverse-variance weights and REML/PL estimation of variance components for the random effects. We introduce new moment-based point and interval estimators for the two variance components and related estimators of the overall mean. Similar to traditional analysis of variance, our method is based on two conditional $Q$ statistics with effective-sample-size weights. We study, by simulation, bias and coverage of these new estimators. For comparison, we also study bias and coverage of the REML/PL-based approach as implemented in {\it rma.mv} in {\it metafor}. Our results demonstrate that the new methods are often considerably better and do not have convergence problems, which plague the standard analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_00795 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Simulations for estimation of random effects and overall effect in three-level meta-analysis of standardized mean differences using constant and inverse-variance weights Kulinskaya, Elena Hoaglin, David C. Methodology We consider a three-level meta-analysis of standardized mean differences. The standard method of estimation uses inverse-variance weights and REML/PL estimation of variance components for the random effects. We introduce new moment-based point and interval estimators for the two variance components and related estimators of the overall mean. Similar to traditional analysis of variance, our method is based on two conditional $Q$ statistics with effective-sample-size weights. We study, by simulation, bias and coverage of these new estimators. For comparison, we also study bias and coverage of the REML/PL-based approach as implemented in {\it rma.mv} in {\it metafor}. Our results demonstrate that the new methods are often considerably better and do not have convergence problems, which plague the standard analysis. |
| title | Simulations for estimation of random effects and overall effect in three-level meta-analysis of standardized mean differences using constant and inverse-variance weights |
| topic | Methodology |
| url | https://arxiv.org/abs/2411.00795 |