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#' Object Summary
#'
#' Generic \code{summary} function for the \code{aovrasch} object
#'
#' @param object \code{aovrasch} object
#' @param ... Additional arguments affecting the summary produced.
#'
#' @author
#' Takuya Yanagida \email{takuya.yanagida@@univie.ac.at},
#' Jan Steinfeld \email{jan.steinfeld@@univie.ac.at}
#'
#' @importFrom stats printCoefmat
#'
#' @export
#'
#' @examples
#' \dontrun{
#'
#' # simulate Rasch model based data
#' # 100 persons, 20 items,
#' dat <- simul.rasch(100, items = seq(-3, 3, length.out = 20))
#' # reshape simulated data into 'long' format with balanced assignment
#' # of examinees into two subgroups.
#' dat.long <- reshape.rasch(dat, group = rep(0:1, each = nrow(dat) / 2))
#' # apply three-way analysis of variance with mixed classification for testing the Rasch model.
#' res <- aov.rasch(dat.long)
#' summary(res)
#' }
summary.aovrasch <- function(object, ...) {
cat("\nThree-way analysis of variance with mixed classification \n\n")
printCoefmat(object[4, , drop = FALSE], has.Pvalue = TRUE, cs.ind = 0)
cat("\n")
# Warning: Statistically significant Main Effect A
if (object[1, "Pr(>F)"] < .05) {
warning(paste0("Main effect A (group) is statistically significant, ",
"F(1, ", object[2, "DF"], ") = ", formatC(object[1, "F value"], format = "f", digits = 3),
", p = ", formatC(object[1, "Pr(>F)"], format = "f", digits = 3), ", i.e. results may not be trustworthy."))
}
}
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