{ "_id": "6a1ffdb8b401979e7344524d", "Package": "mmeta", "Type": "Package", "Title": "Multivariate Meta-Analysis", "Version": "3.0.2", "Date": "2025-06-07", "Authors@R": "c(person(\"Sheng\", \"Luo\", role=\"aut\"), \nperson(\"Yong\", \"Chen\", role =\"aut\", email = \"ychen123@pennmedicine.upenn.edu\" ),\nperson(\"Xiao\", \"Su\", role = \"aut\"),\nperson(\"Haitao\", \"Chu\", role = \"aut\"),\nperson(\"Bingyu\", \"Zhang\", role = \"cre\", email = \"bingyuz7@sas.upenn.edu\"),\nperson(\"Wally\", \"Gilks\", role = \"ctb\"),\nperson(\"Giovanni\", \"Petris\", role = \"ctb\"),\nperson(\"Luca\", \"Tardella\", role = \"ctb\"))", "Maintainer": "Bingyu Zhang ", "Description": "Multiple 2 by 2 tables often arise in meta-analysis which\ncombines statistical evidence from multiple studies. Two risks\nwithin the same study are possibly correlated because they\nshare some common factors such as environment and population\nstructure. This package implements a set of novel Bayesian\napproaches for multivariate meta analysis when the risks within\nthe same study are independent or correlated. The exact\nposterior inference of odds ratio, relative risk, and risk\ndifference given either a single 2 by 2 table or multiple 2 by\n2 tables is provided. 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