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Bayesian Nonparametric Bivariate Meta Analysis | ||
| Journal of Data Science and Modeling | ||
| مقاله 9، دوره 1، شماره 1، اسفند 2022، صفحه 129-141 اصل مقاله (348.53 K) | ||
| نوع مقاله: Research Manuscript | ||
| شناسه دیجیتال (DOI): 10.22054/jcsm.2018.36484.1013 | ||
| نویسنده | ||
| Ehsan Ormoz* | ||
| Department of Mathematics and Statistics, Mashhad Branch, Islamic Azad University | ||
| چکیده | ||
| In the meta-analysis of clinical trials, usually the data of each trail summarized by one or more outcome measure estimates which reported along with their standard errors. In the case that summary data are multi-dimensional, usually, the data analysis will be performed in the form of a number of separated univariate analysis. In such a case the correlation between summary statistics would be ignored. In contrast, a multivariate meta-analysis model, use from these correlations synthesizes the outcomes, jointly to estimate the multiple pooled effects simultaneously. In this paper, we present a nonparametric Bayesian bivariate random effect meta-analysis. | ||
| کلیدواژهها | ||
| Bayesian Nonparametric؛ Gibbs algorithm؛ Meta-analysis؛ Bivariate Distribution؛ Bayesian Model Selection | ||
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آمار تعداد مشاهده مقاله: 462 تعداد دریافت فایل اصل مقاله: 779 |
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