#' Summary method for Copas selection model
#'
#' Summary method for objects of class \code{copas}.
#'
#' This function complements the graphical summary of the results of a
#' Copas selection model, generated using \code{plot.copas}.
#'
#' @aliases summary.copas
#'
#' @param object An object of class \code{copas}.
#' @param ... other arguments to the function will be ignored (this
#' option included only to conform with R standards)
#'
#' @return An object of class "summary.copas" with corresponding print
#' function. The object is a list containing the following
#' components:
#'
#' \item{slope}{Results for points on orthogonal line (a list with
#' elements TE, seTE, lower, upper, statistic, p, level).}
#' \item{publprob}{Vector of probabilities of publishing the smallest
#' study.}
#' \item{pval.rsb}{P-values for tests on presence of residual
#' selection bias}
#' \item{N.unpubl}{Approximate number of studies the model suggests
#' remain unpublished}
#' \item{adjust}{Result of Copas selection model adjusted for
#' selection bias (a list with elements TE, seTE, lower, upper,
#' statistic, p, level).}
#' \item{sign.rsb}{The significance level for the test of residual
#' selection bias.}
#' \item{pval.rsb.adj}{P-value for test on presence of residual
#' selection bias for adjusted effect given in \code{adjust}.}
#' \item{N.unpubl.adj}{Approximate number of studies the model
#' suggests remain unpublished for adjusted effect given in
#' \code{adjust}}
#' \item{random}{Results for usual random effects model (a list with
#' elements TE, seTE, lower, upper, statistic, p, level).}
#' \item{sm}{A character string indicating underlying summary
#' measure.}
#' \item{ci.lab}{Label for confidence interval.}
#' \item{title}{Title of meta-analysis / systematic review.}
#' \item{complab}{Comparison label.} \item{outclab}{Outcome label.}
#' \item{version}{Version of R package metasens used to create
#' object.}
#'
#' @author James Carpenter \email{James.Carpenter@@lshtm.ac.uk}, Guido
#' Schwarzer \email{guido.schwarzer@@uniklinik-freiburg.de}
#'
#' @seealso \code{\link{copas}}, \code{\link{plot.copas}},
#' \code{\link[meta]{metabias}}, \code{\link[meta]{metagen}}
#'
#' @examples
#' data(Fleiss1993bin, package = "meta")
#'
#' # Perform meta analysis, effect measure is odds ratio (OR)
#' #
#' m1 <- metabin(d.asp, n.asp, d.plac, n.plac, data = Fleiss1993bin, sm = "OR")
#'
#' # Print summary of Copas analysis
#' #
#' summary(copas(m1, level.ma = 0.95))
#'
#' @method summary copas
#' @export
#' @export summary.copas
summary.copas <- function(object, ...) {
chkclass(object, "copas")
ci.random <- list(TE = object$TE.random,
seTE = object$seTE.random,
lower = object$lower.random,
upper = object$upper.random,
statistic = object$statistic.random,
p = object$pval.random,
level = object$level.ma)
##
ci.slope <- list(TE = object$TE.slope,
seTE = object$seTE.slope,
lower = object$lower.slope,
upper = object$upper.slope,
statistic = object$statistic.slope,
p = object$pval.slope,
level = object$level.ma)
##
ci.adjust <- list(TE = object$TE.adjust,
seTE = object$seTE.adjust,
lower = object$lower.adjust,
upper = object$upper.adjust,
statistic = object$statistic.adjust,
p = object$pval.adjust,
level = object$level.ma)
##
ci.lab <- paste(round(100 * object$level.ma, 1), "%-CI", sep = "")
res <- list(slope = ci.slope,
publprob = object$publprob,
pval.rsb = object$pval.rsb,
N.unpubl = object$N.unpubl,
adjust = ci.adjust,
sign.rsb = object$sign.rsb,
pval.rsb.adj = object$pval.rsb.adj,
N.unpubl.adj = object$N.unpubl.adj,
random = ci.random,
sm = object$sm,
ci.lab = ci.lab,
x = object
)
class(res) <- c("summary.copas")
res$complab <- object$complab
res$outclab <- object$outclab
res$title <- object$title
res$backtransf <- object$backtransf
res$version <- utils::packageDescription("metasens")$Version
res
}
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