R/Woods2010.R

In netmeta: Network Meta-Analysis using Frequentist Methods

#' Count statistics of survival data
#' 
#' @description
#' Count mortality statistics in randomised controlled trials of
#' treatments for chronic obstructive pulmonary disease (Woods et
#' al. (2010), Table 1).
#' 
#' @name Woods2010
#'
#' @docType data
#'
#' @format
#' A data frame with the following columns:
#' \tabular{rl}{
#' \bold{\emph{author}}\tab first author / study name \cr
#' \bold{\emph{treatment}}\tab treatment \cr
#' \bold{\emph{r}}\tab number of deaths in treatment arm \cr
#' \bold{\emph{N}}\tab number of patients in treatment arm
#' }
#' 
#' @seealso \code{\link{pairwise}}, \code{\link{metabin}},
#'   \code{\link{netmeta}}
#' 
#' @source
#' Woods BS, Hawkins N, Scott DA (2010):
#' Network meta-analysis on the log-hazard scale, combining count and
#' hazard ratio statistics accounting for multi-arm trials: A
#' tutorial.
#' \emph{BMC Medical Research Methodology},
#' \bold{10}, 54
#' 
#' @keywords datasets
#' 
#' @examples
#' data(Woods2010)
#' 
#' # Transform data from long arm-based format to contrast-based
#' # format Argument 'sm' has to be used for odds ratio as summary
#' # measure; by default the risk ratio is used in the metabin
#' # function called internally.
#' #
#' p1 <- pairwise(treatment, event = r, n = N,
#'   studlab = author, data = Woods2010, sm = "OR")
#' p1
#' 
#' # Conduct network meta-analysis
#' #
#' net1 <- netmeta(p1)
#' net1
#' 
#' \dontrun{
#' # Show forest plot
#' #
#' forest(net1, ref = "Placebo", drop = TRUE,
#'   leftlabs = "Contrast to Placebo")
#' }


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