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A Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons
Bayesian statistical approaches to mixed treatment comparisons (MTCs) are becoming more popular due to their flexibility and interpretability. Many randomized clinical trials report multiple outcomes with possible inherent correlations. Moreover, MTC data are typically sparse (though richer than sta...
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| 出版年: | Res Synth Methods |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2015
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4779385/ https://ncbi.nlm.nih.gov/pubmed/26536149 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/jrsm.1153 |
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