#' Generic function for network graphs
#'
#' @description
#' Generic function for network graphs
#'
#' @param x An R object.
#' @param \dots Additional arguments.
#'
#' @details
#'
#' For more details, look at the following functions to generate
#' network graphs:
#' \itemize{
#' \item \code{\link{netgraph.netmeta}}
#' \item \code{\link{netgraph.netimpact}}
#' \item \code{\link{netgraph.netconnection}}
#' \item \code{\link{netgraph.netcomb}}
#' \item \code{\link{netgraph.discomb}}
#' }
#'
#' @author Guido Schwarzer \email{guido.schwarzer@@uniklinik-freiburg.de
#' }
#'
#' @keywords hplot
#'
#' @examples
#' data(smokingcessation)
#'
#' # Transform data from arm-based format to contrast-based format
#' #
#' p1 <- pairwise(list(treat1, treat2, treat3),
#' event = list(event1, event2, event3), n = list(n1, n2, n3),
#' data = smokingcessation, sm = "OR")
#'
#' # Conduct random effects network meta-analysis
#' #
#' net1 <- netmeta(p1, common = FALSE)
#'
#' # Network graph with default settings
#' #
#' netgraph(net1)
#'
#' \dontrun{
#' data(Senn2013)
#'
#' # Generation of an object of class 'netmeta' with reference
#' # treatment 'plac'
#' #
#' net2 <- netmeta(TE, seTE, treat1, treat2, studlab,
#' data = Senn2013, sm = "MD", reference = "plac")
#'
#' # Network graph with default settings
#' #
#' netgraph(net2)
#'
#' data(Woods2010)
#' p3 <- pairwise(treatment, event = r, n = N,
#' studlab = author, data = Woods2010, sm = "OR")
#' net3 <- netmeta(p3)
#'
#' # Network graph with default settings
#' #
#' netgraph(net3)
#'
#' # Network graph with
#' # - number of studies for each pairwise comparison and
#' # - number of participants for each treatment arm
#' #
#' netgraph(net3, number.of.studies = TRUE,
#' labels = paste0(trts, " (n=", n.trts, ")"))
#' }
#'
#' @rdname netgraph
#' @export netgraph
netgraph <- function(x, ...)
UseMethod("netgraph")
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