R/Senn2013.R

In netmeta: Network Meta-Analysis using Frequentist Methods

#' Network meta-analysis in diabetes
#' 
#' @description
#' Network meta-analysis in diabetes comparing effects of a number of
#' drugs on the HbA1c value.
#' 
#' These data are used as an example in Senn et al. (2013) and have been
#' preprocessed for use in R package netmeta.
#' 
#' @name Senn2013
#' 
#' @docType data
#' 
#' @details
#' Treatment labels provided by columns \code{treat1} and
#' \code{treat2} have been abbreviated:
#' \itemize{
#' \item acar = Acarbose
#' \item benf = Benfluorex
#' \item metf = Metformin
#' \item migl = Miglitol
#' \item piog = Pioglitazone
#' \item plac = Placebo
#' \item rosi = Rosiglitazone
#' \item sita = Sitagliptin
#' \item sulf = Sulfonylurea
#' \item vild = Vildagliptin
#' }
#'
#' Full treatment names are available in columns \code{treat1.long}
#' and \code{treat2.long}.
#' 
#' @format
#' A data frame with the following columns:
#' \tabular{rl}{
#' \bold{\emph{TE}}\tab treatment effect \cr
#' \bold{\emph{seTE}}\tab standard error of treatment effect \cr
#' \bold{\emph{treat1}}\tab treatment 1 \cr
#' \bold{\emph{treat2}}\tab treatment 2 \cr
#' \bold{\emph{treat1.long}}\tab treatment 1 (full treatment names)
#'   \cr
#' \bold{\emph{treat2.long}}\tab treatment 2 (full treatment names)
#'   \cr
#' \bold{\emph{studlab}}\tab Study label
#' }
#' 
#' @seealso \code{\link{netmeta}}
#' 
#' @source
#' Senn S, Gavini F, Magrez D, Scheen A (2013):
#' Issues in performing a network meta-analysis.
#' \emph{Statistical Methods in Medical Research},
#' \bold{22}, 169--89
#' 
#' @keywords datasets
#' 
#' @examples
#' data(Senn2013)
#' head(Senn2013)
#' 
#' \dontrun{
#' # Common effects model
#' #
#' net1 <- netmeta(TE, seTE, treat1.long, treat2.long, studlab,
#'   data = Senn2013, sm = "MD", random = FALSE, nchar.trts = 4)
#' net1
#' net1$Q.decomp
#' 
#' # Forest plot
#' #
#' forest(net1, ref = "plac")
#' 
#' # Comparison with reference group
#' #
#' netmeta(TE, seTE, treat1.long, treat2.long,
#'   studlab, data = Senn2013, reference = "plac")
#' 
#' # Random effects model
#' #
#' net2 <- netmeta(TE, seTE, treat1.long, treat2.long, studlab,
#'   data = Senn2013, common = FALSE)
#' net2
#' forest(net2, ref = "plac")
#' }


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