R/plot.summary.lmw.R

In lmw: Linear Model Weights

#' Produce a Love plot of balance statistics
#'
#' @description
#' Produces Love plots (also known as dot plots) of balance statistics to
#' summarize balance visually. The plots are generated using
#' [dotchart()] and [points()].
#'
#' @details
#' Love plots will be produced for the requested statistics in the
#' `summary.lmw` output. How these plots are arranged depends on the value
#' supplied to `layout`, which uses [layout()] to arrange the
#' plots.
#'
#' @param x a `summary.lmw` object; the output of a call to
#' [summary.lmw()] with `standardize = TRUE`.
#' @param stats a vector of the names of the columns in the `summary.lmw`
#' output to plot; more than one is allowed. Abbreviations allowed. When
#' unspecified, the TSMD statistics for each treatment group will be plotted.
#' @param abs `logical`; whether the statistics should be plotted in
#' absolute value (`TRUE`) or not (`FALSE`). Default is `TRUE`.
#' This does not affect the display of KS statistics (which are always
#' non-negative). When `TRUE` and standardized mean differences are
#' displayed, the x-axis title will be "TASMD", i.e., target absolute
#' standardized mean difference.
#' @param var.order how the variables should be ordered. Allowable options
#' include `"data"`, ordering the variables as they appear in the summary
#' output, `"alphabetical"`, ordering the variables alphabetically, and,
#' when `un = TRUE` in the call to `summary.lmw()`,
#' `"unadjusted"`, ordering the variables by the first statistic in
#' `stats` in the unadjusted sample. Default is `"data"`.
#' Abbreviations allowed.
#' @param threshold numeric values at which to place vertical lines indicating
#' a balance threshold. These can make it easier to see for which variables
#' balance has been achieved given a threshold. Multiple values can be supplied
#' to add multiple lines. When `abs = FALSE`, the lines will be displayed
#' on both sides of zero. The lines are drawn with `abline` with the
#' linetype (`lty`) argument corresponding to the order of the entered
#' variables (see options at [par()]). Enter a value as `NA` to
#' skip that value of `lty` (e.g., `c(NA, .05)` to have only a dashed
#' vertical line at .05).
#' @param layout how the multiple plots should be laid out. Allowable options
#' include `"vertical"` (the default) and `"horizontal"`.
#' Abbreviations allowed.
#' @param \dots further arguments passed to [dotplot()].
#'
#' @return A plot is displayed, and `x` is invisibly returned.
#'
#' @seealso [summary.lmw()]
#'
#' @examples
#' data("lalonde")
#'
#' # URI regression for ATT
#' lmw.out1 <- lmw(~ treat + age + education + race + married +
#'                   nodegree + re74 + re75, data = lalonde,
#'                 estimand = "ATT", method = "URI",
#'                 treat = "treat")
#' lmw.out1
#' (s <- summary(lmw.out1))
#'
#' plot(s)
#' plot(s, stats = "SMD", abs = FALSE)

#' @exportS3Method plot summary.lmw
plot.summary.lmw <- function(x, stats, abs = TRUE, var.order = "data", threshold = NULL, layout = "vertical", ...) {
  .pardefault <- par(no.readonly = TRUE)
  on.exit(par(.pardefault))

  un <- !is.null(x[["bal.un"]])
  base.weighted <- !is.null(x[["bal.base.weighted"]])
  weighted <- !is.null(x[["bal.weighted"]])

  if (!un && !base.weighted && !weighted) {
    chk::err("`plot()` can only be used on summary.lmw objects when `stat = \"balance\"` was specified in the call to `summary()`")
  }

  standard.sum <- if (un) x[["bal.un"]] else x[["bal.weighted"]]

  if (!any(startsWith(colnames(standard.sum), "TSMD"))) {
    chk::err("not appropriate for unstandardized summary. Run `summary()` with the `standardize = TRUE` option, and then plot")
  }

  if (missing(stats)) {
    stats <- colnames(standard.sum)[startsWith(colnames(standard.sum), "TSMD")]
  }
  stats <- match_arg(stats, colnames(standard.sum), several.ok = TRUE)

  if (un) {
    stats.un <- as.data.frame(x[["bal.un"]][,stats, drop = FALSE])
  }
  if (base.weighted) {
    stats.base.weighted <- as.data.frame(x[["bal.base.weighted"]][,stats, drop = FALSE])
  }
  if (weighted) {
    stats.weighted <- as.data.frame(x[["bal.weighted"]][,stats, drop = FALSE])
  }

  var.names <- rownames(standard.sum)

  chk::chk_string(var.order)
  var.order <- tolower(var.order)
  var.order <- match_arg(var.order, c("data", "alphabetical", "unadjusted"[un]))

  chk::chk_string(layout)
  layout <- tolower(layout)
  layout <- match_arg(layout, c("vertical", "horizontal"))

  chk::chk_flag(abs)

  if (abs) {
    if (un) {
      for (i in seq_along(stats.un))
        stats.un[[i]] <- abs(stats.un[[i]])
    }
    if (base.weighted) {
      for (i in seq_along(stats.base.weighted))
        stats.base.weighted[[i]] <- abs(stats.base.weighted[[i]])
    }
    if (weighted) {
      for (i in seq_along(stats.weighted))
        stats.weighted[[i]] <- abs(stats.weighted[[i]])
    }
  }

  xlab <- vapply(stats, rename_summary_stat, character(1L), abs = abs)

  ord <- switch(var.order,
                "data" = rev(seq_along(var.names)),
                "alphabetical" = order(var.names, decreasing = TRUE),
                "unadjusted" = order(stats.un[[1]]))

  minx <- min(if (un) unlist(stats.un), if (base.weighted) unlist(stats.base.weighted), if (weighted) unlist(stats.weighted), if (abs) 0 else -.01)
  maxx <- max(if (un) unlist(stats.un), if (base.weighted) unlist(stats.base.weighted), if (weighted) unlist(stats.weighted), .01)

  xlim <- c(minx, 1.75*maxx - minx)

  if (layout == "vertical") layout(do.call("rbind", as.list(seq_along(stats))))
  else if (layout == "horizontal") layout(do.call("cbind", as.list(seq_along(stats))))

  par(mar=c(3.75, 6.5, 1.25, 0.5),
      mgp=c(1.5, 0.5, 0))

  if (base.weighted) {
    if (identical(x$base.weights.origin, "MatchIt")) {
      legend.text <- sprintf(c("Before matching"[un],
                               "After matching",
                               "After matching + \n%s regression"[weighted]), x$method)
    }
    else if (identical(x$base.weights.origin, "WeightIt")) {
      legend.text <- sprintf(c("Before weighting"[un],
                               "After weighting",
                               "After weighting + \n%s regression"[weighted]), x$method)
    }
    else {
      legend.text <- sprintf(c("Before base weighting"[un],
                               "After base weighting",
                               "After base weighting + \n%s regression"[weighted]), x$method)
    }
  }
  else {
    legend.text <- sprintf(c("Before regression"[un],
                             "After %s regression"[weighted]), x$method)
  }


  for (i in seq_along(stats)) {
    dotchart(if (un) stats.un[[i]][ord] else stats.weighted[[i]][ord],
             labels = var.names[ord], xlab = xlab[[i]],
             xlim = xlim, lcolor = NA,
             cex=.8,
             bg = NA, color = NA, ...)
    abline(v = 0)

    if (un) {
      points(x = stats.un[[i]][ord], y = seq_along(stats.un[[i]]),
             pch = 4, cex=1.5)
    }
    if (base.weighted) {
      points(x = stats.base.weighted[[i]][ord], y = seq_along(stats.base.weighted[[i]]),
             pch = 1, cex=1.5)
    }
    if (weighted) {
      points(x = stats.weighted[[i]][ord], y = seq_along(stats.weighted[[i]]),
             pch = 19, cex=1.5)
    }

    if (!is.null(threshold)) {
      if (abs) {
        abline(v = threshold, lty = seq_along(threshold))
      }
      else {
        abline(v = threshold, lty = seq_along(threshold))
        abline(v = -threshold, lty = seq_along(threshold))
      }
    }

    # title(ylab = "Covariate", mgp = c(5.25, 0.5, 0), cex = .8)

    legend(x=maxx + .1*(maxx-minx),
           y=length(var.names)+0.65,
           legend=legend.text,
           pch=c(4, 1, 19)[c(un, base.weighted, weighted)],
           bty="n",
           cex = .8)
  }

  invisible(x)
}

rename_summary_stat <- function(x, abs = FALSE) {
  splitted <- strsplit(x, " ", fixed = TRUE)[[1]]
  stat <- splitted[1]
  if (endsWith(stat, "KS")) stat <- paste(stat, "statistic")
  else if (endsWith(stat, "SMD") && abs) stat <- sub("SMD", "ASMD", stat, fixed = TRUE)

  if (length(splitted) == 1) return(stat)

  group <- paste(splitted[-1], collapse = " ")
  if (tolower(group) %in% c("treated", "control")) {
    group <- paste(tolower(group), "group")
  }
  sprintf("%s (%s)", stat, group)
}