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#' @title print.multisimsum
#' @description Print method for multisimsum objects
#' @param x An object of class `multisimsum`.
#' @param ... Ignored.
#' @export
#'
#' @examples
#' data(frailty)
#' ms <- multisimsum(
#' data = frailty, par = "par", true = c(
#' trt = -0.50,
#' fv = 0.75
#' ), estvarname = "b", se = "se", methodvar = "model",
#' by = "fv_dist"
#' )
#' ms
#'
#' data("frailty", package = "rsimsum")
#' frailty$true <- ifelse(frailty$par == "trt", -0.50, 0.75)
#' ms <- multisimsum(data = frailty, par = "par", estvarname = "b", true = "true")
#' ms
print.multisimsum <- function(x, ...) {
### Print `par`, possible estimands
cat("\nEstimands variable:", x$par, "\n")
estimands <- unique(x$summ[[x$par]])
cat("\tUnique estimands:", paste(estimands, collapse = ", "), "\n")
if (!is.null(x$true)) {
if (rlang::is_named(x$true)) {
cat("\tTrue values:", paste(estimands, "=", x$true[estimands], collapse = ", "), "\n")
} else {
if (is.character(x$true)) {
cat("\tTrue values from column", paste0("'", x$true, "'"), "\n")
} else {
cat("\tTrue values fixed at value", x$true, "\n")
}
}
} else {
cat("\tTrue value of the estimands not defined: bias, relative bias, coverage, and mean squared error were not computed.\n")
}
### Print `methodvar` (if any), possible methods, and reference method
if (!is.null(x$methodvar)) {
if (length(x$methodvar) > 1) {
cat("\nColumns identifying methods:", paste(x$methodvar, collapse = ", "), "\n")
reftable <- .compact_method_columns(data = tidy.multisimsum(x), methodvar = x$methodvar)$data[[":methodvar"]]
cat("\tUnique methods:", paste(unique(reftable), collapse = ", "), "\n")
} else {
cat("\nMethod variable:", x$methodvar, "\n")
methods <- unique(x$summ[[x$methodvar]])
cat("\tUnique methods:", paste(methods, collapse = ", "), "\n")
cat("\tReference method:", x$ref, "\n")
}
} else {
cat("\nMethod variable: none\n")
}
### Print `by` factors (if any)
if (!is.null(x$by)) {
cat("\nBy factors:", paste(x$by, collapse = ", "), "\n")
} else {
cat("\nBy factors: none\n")
}
### Print whether Monte Carlo SEs were computed or not
if (x$control$mcse) {
cat("\nMonte Carlo standard errors were computed.\n")
} else {
cat("\nMonte Carlo standard errors were not computed.\n")
}
}
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