Bayesian Random‐Effects Meta‐Analysis of Aggregate Data on Clinical Events
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Wiley Open Access
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| Natura: | Artículo Open Access |
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Wiley
2026
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| _version_ | 1867020385547976704 |
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| author | Christian Röver Qiong Wu Anja Loos Tim Friede |
| author_facet | Christian Röver Qiong Wu Anja Loos Tim Friede Christian Röver Qiong Wu Anja Loos Tim Friede |
| collection | Wiley Open Access |
| contents | Bayesian Random‐Effects Meta‐Analysis of Aggregate Data on Clinical Events Christian Röver Qiong Wu Anja Loos Tim Friede Statistics in Medicine ABSTRACT To investigate intervention effects on rare events, meta‐analysis techniques are commonly applied in order to assess the accumulated evidence. When it comes to adverse effects in clinical trials, these are often most adequately handled using survival methods. A common‐effect model that is able to process data in commonly quoted formats in terms of hazard ratios has previously been proposed for this purpose. In order to accommodate potential heterogeneity between studies, we have extended the model by Holzhauer to a random‐effects approach. The Bayesian model is described in detail, and applications to realistic data sets are discussed along with sensitivity analyses and Monte Carlo simulations to support the conclusions. 10.1002/sim.70508 http://creativecommons.org/licenses/by/4.0/ |
| doi_str_mv | 10.1002/sim.70508 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_sim_70508 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| publishDate | 2026 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Bayesian Random‐Effects Meta‐Analysis of Aggregate Data on Clinical Events Christian Röver Qiong Wu Anja Loos Tim Friede Statistics in Medicine Bayesian Random‐Effects Meta‐Analysis of Aggregate Data on Clinical Events Christian Röver Qiong Wu Anja Loos Tim Friede Statistics in Medicine ABSTRACT To investigate intervention effects on rare events, meta‐analysis techniques are commonly applied in order to assess the accumulated evidence. When it comes to adverse effects in clinical trials, these are often most adequately handled using survival methods. A common‐effect model that is able to process data in commonly quoted formats in terms of hazard ratios has previously been proposed for this purpose. In order to accommodate potential heterogeneity between studies, we have extended the model by Holzhauer to a random‐effects approach. The Bayesian model is described in detail, and applications to realistic data sets are discussed along with sensitivity analyses and Monte Carlo simulations to support the conclusions. 10.1002/sim.70508 http://creativecommons.org/licenses/by/4.0/ |
| title | Bayesian Random‐Effects Meta‐Analysis of Aggregate Data on Clinical Events |
| topic | Statistics in Medicine |
| url | https://onlinelibrary.wiley.com/doi/10.1002/sim.70508 |