mean_comparisons.check_model_anova.R

#' Get mean comparisons from \code{\link{check_model.fit_model_anova}} object
#'
#' @description
#' \code{mean_comparisons} performs mean comparisons from object coming from \code{\link{check_model.fit_model_anova}}
#'
#' @param x outputs from \code{\link{check_model.fit_model_anova}}
#' 
#' @param alpha level of type one error. 0.05 (5\%) by default
#' 
#' @param p.adj For all except type = 2. 
#' NULL for no adjustement of the type one error. 
#' p.adj can "holm", "hochberg", "bonferroni", "BH", "BY" or "fdr"
#' p-adj = "none" is t-student.
#' See p.adjust() for more details.
#' 
#' @param ... further arguments passed to or from other methods
#' 
#' @details
#' S3 method.
#' See in the book for more details \href{https://priviere.github.io/PPBstats_book/intro-agro.html#section-freq}{here}
#' 
#' @return 
#'  A list of four elements : 
#'   \itemize{
#'    \item info : a list with variable
#'   }
#' 
#' @author Pierre Riviere
#' 
#' @seealso 
#' \itemize{
#'  \item \code{\link{mean_comparisons}}
#'  \item \code{\link{plot.PPBstats}}
#'  \item \code{\link{plot.mean_comparisons_model_anova}}
#' }
#' 
#' @export
#' 
mean_comparisons.check_model_anova <- function(
  x, 
  alpha = 0.05,
  p.adj = "none",
  ...
){
  out = mean_comparisons_freq_anova(model = x$model_anova$ANOVA$model, 
                                    variable = x$model_anova$info$variable, 
                                    alpha, p.adj, info = x$info, vec_fac = "germplasm")
  class(out) <- c("PPBstats", "mean_comparisons_model_anova")
  return(out)
}