#' Cochrane review: summary of meta-analyses
#'
#' @description
#' Calculate and print a summary of all meta-analyses in a
#' Cochrane review.
#'
#' @param x An object of class \code{rm5}.
#' @param comp.no Comparison number.
#' @param outcome.no Outcome number.
#' @param ... Additional arguments (passed on to \code{metacr}).
#'
#' @details
#' This function can be used to redo all or selected meta-analyses of
#' a Cochrane Review of interventions (Higgins et al., 2023).
#'
#' Review Manager 5 (RevMan 5) was the software used for preparing and
#' maintaining Cochrane Reviews
#' (\url{https://training.cochrane.org/online-learning/core-software/revman}).
#' In RevMan 5, subgroup analyses can be defined and data from a
#' Cochrane review can be imported to R using the function
#' \code{read.rm5}.
#'
#' The R function \code{\link{metacr}} is called internally.
#'
#' @author Guido Schwarzer \email{guido.schwarzer@@uniklinik-freiburg.de}
#'
#' @seealso \code{\link{summary.meta}}, \code{\link{metacr}},
#' \code{\link{read.rm5}}, \code{\link{metabias.rm5}}
#'
#' @references
#' Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch
#' VA (editors) (2023):
#' \emph{Cochrane Handbook for Systematic Reviews of Interventions
#' Version 6.4 (updated August 2023)}.
#' Available from \url{https://www.training.cochrane.org/handbook}
#'
#' @examples
#' # Locate export data file "Fleiss1993_CR.csv"
#' # in sub-directory of package "meta"
#' #
#' filename <- system.file("extdata", "Fleiss1993_CR.csv", package = "meta")
#' Fleiss1993_CR <- read.rm5(filename)
#'
#' # Print results for all meta-analysis
#' #
#' Fleiss1993_CR
#'
#' # Print results only for second outcome of first comparison
#' #
#' print(Fleiss1993_CR, comp.no = 1, outcome.no = 2)
#'
#' @method print rm5
#' @export
print.rm5 <- function(x, comp.no, outcome.no, ...) {
##
##
## (1) Check for rm5 object
##
##
chkclass(x, "rm5")
if (missing(comp.no))
comp.no <- unique(x$comp.no)
##
res <- list()
##
n <- 1
##
for (i in comp.no) {
if (missing(outcome.no))
jj <- unique(x$outcome.no[x$comp.no == i])
else
jj <- outcome.no
for (j in jj) {
##
res[[n]] <- metacr(x, i, j, ...)
##
n <- n + 1
}
}
##
n <- 1
##
for (i in seq_len(length(res))) {
if (n > 1)
cat("\n*****\n\n")
print(res[[n]])
n <- n + 1
}
invisible(NULL)
}
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