{ "_id": "6a156d0eacfb0bcc41d6422f", "Package": "simdistr", "Type": "Package", "Title": "Assessment of Data Trial Distributions According to the\nCarlisle-Stouffer Method", "Version": "1.0.1", "Authors@R": "c(person(\"Bernardo\",\"Sousa-Pinto\",role=c(\"aut\",\"cre\"),email=\"bernardo@med.up.pt\"),\nperson(\"Joao Julio\",\"Cerqueira\",role=\"ctb\"),\nperson(\"Cristina\",\"Costa-Santos\",role=\"ctb\"),\nperson (\"John B\",\"Carlisle\",role=\"ctb\"),\nperson (\"John A\",\"Loadsman\",role=\"ctb\"),\nperson(\"Armando\",\"Teixeira-Pinto\",role=\"aut\"),\nperson(\"Hernani\",\"Goncalves\",role=\"aut\"))", "Author": "Bernardo Sousa-Pinto [aut, cre], Joao Julio Cerqueira [ctb],\nCristina Costa-Santos [ctb], John B Carlisle [ctb], John A\nLoadsman [ctb], Armando Teixeira-Pinto [aut], Hernani Goncalves\n[aut]", "Maintainer": "Bernardo Sousa-Pinto ", "Description": "Assessment of the distributions of baseline continuous and\ncategorical variables in randomised trials. This method is\nbased on the Carlisle-Stouffer method with Monte Carlo\nsimulations. It calculates p-values for each trial baseline\nvariable, as well as combined p-values for each trial - these\np-values measure how compatible are distributions of trials\nbaseline variables with random sampling. This package also\nallows for graphically plotting the cumulative frequencies of\ncomputed p-values. Please note that code was partly adapted\nfrom Carlisle JB, Loadsman JA. 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