R/anticoagulation.R

In metainc: Assessment of Inconsistency in Meta-Analysis using Decision Thresholds

#' Sampled odds ratios from meta-analysis on the association between
#' parenteral anticoagulation and mortality in patients with cancer
#' 
#' @description
#' Matrix with sampled odds ratios from meta-analysis on the association
#' between parenteral anticoagulation and mortality in patients with cancer
#' (Akl et al., 2017).
#' 
#' @name anticoagulation
#' @aliases anticoagulation
#' 
#' @docType data
#' 
#' @format A matrix with 5000 sampled odds ratios (rows) for 18 studies
#' (columns) following a Bayesian meta-analysis.
#' 
#' @details
#' Data  from Akl et al. (2017) and displaying results presented as odds ratios. 
#' Each column corresponds to a different primary study.
#' 
#' @source
#' Akl, E. A., Kahale, L. A., Hakoum, M. B., Matar, C. F., Sperati, F.,
#' Barba, M., et al. (2017).
#' \dQuote{Parenteral anticoagulation in ambulatory patients with cancer.}
#' \emph{Cochrane Database of Systematic Reviews},
#' \bold{9}: CD006652.
#'
#' @keywords datasets
#' 
#' @seealso \code{\link{inc}}, \code{\link{anticoagulation_df}}
#'
#' @examples
#' 
#' data(anticoagulation)
#' 
#' # Since the results are already presented as odds ratios, we need
#' # to indicate that effects have not been transformed to log odds
#' # ratios yet (\code{transf = FALSE}).
#' dis1 <- inc(anticoagulation, br = 0.504, dt1 = 16, sm = "OR",
#'   transf = FALSE)
#' dis1
#' 
#' # Alternatively, we may simply apply the \code{inc()} function to
#' # log odds ratios.
#' data(anticoagulation)
#' dis2 <- inc(log(anticoagulation), br = 0.504, dt1 = 16, sm = "OR")
#' dis2

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