S3 dispatch examples for R packages

s3_tutorial.R

library(psychmeta)
ma_obj <- ma_r(rxyi = rxyi, n = n, rxx = rxxi, ryy = ryyi,
               construct_x = x_name, construct_y = y_name, sample_id = sample_id,
               moderators = moderator, data = data_r_meas_multi)
summary(ma_obj)

class(ma_obj)

inherits(ma_obj, "ma_psychmeta")
inherits(ma_obj, "ma_table")
inherits(ma_obj, "data.frame")


print <- function (x, ...) {
  UseMethod("print")
}

#' @export
#' @keywords internal
#' @method print ad_tsa
print.ad_tsa <- function(x, ..., digits = 3){
  cat("Taylor-Series Artifact Distributions\n")
  cat("------------------------------------\n")

  print(round(as.matrix(x[,]), digits = digits))

  cat("\n")
  invisible(x)
}

# S3method(print,ad_tsa)
# export(adjust_n_d)

#' @export
#' @importFrom dplyr filter_if
#' @method filter_if ma_psychmeta
filter_if.ma_psychmeta <- function(.tbl, predicate, .vars_predicate){
  original <- .tbl
  modified <- NextMethod()
  modified <- reattribute(x = original, result = modified)
  return(modified)
}


test <- t.test(1:10, y = c(7:20), var.equal = TRUE)
class(test)

#' @export
effectsize <- function(object, ...) {
  UseMethod("effectsize")
}

#' @export
#' @method effectsize htest
effectsize.htest <- function(object, ..., n1 = NULL, n2 = NULL, prop = NULL) {
  if (is.null(prop)) {
    if (! (is.null(n1) && is.null(n2))) {
      prop <- n1 / sum(n1, n1)
    } else {
      prop <- .5
    }
  }
  stat <- object$statistic
  df <- object$parameter
  N <- df + 2
  a <- 1 / (prop * (1 - prop))
  eff_size <- stat * sqrt(a / N)
  conf_int <- ci_cohen_d(...)
  out <- list(eff_size = eff_size, conf_int = conf_int)
  class(out) <- "es_mote"
  return(out)
}