From 9951de2bf103b84d84cf1b559ae6be5fdc52144d Mon Sep 17 00:00:00 2001
From: hanneoberman <h.i.oberman@uu.nl>
Date: Mon, 14 Oct 2024 13:33:40 +0200
Subject: [PATCH 1/2] First draft for `plot_moments` function

---
 R/plot_moments.R | 101 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 R/plot_moments.R

diff --git a/R/plot_moments.R b/R/plot_moments.R
new file mode 100644
index 0000000..bde33cb
--- /dev/null
+++ b/R/plot_moments.R
@@ -0,0 +1,101 @@
+#' Plot the moments of the data and imputed values
+#'
+#' @param data An object of class [mice::mids].
+#' @param vrb String, vector, or unquoted expression with variable name(s),
+#'   default is "all".
+#'
+#' @details
+#' The `vrb` argument is "quoted" via [rlang::enexpr()] and evaluated according
+#' to [tidy evaluation principles](https://adv-r.hadley.nz/metaprogramming.html).
+#' In practice, this technical nuance only affects users when passing an object
+#' from the environment (e.g., a vector of variable names) to the `vrb` argument.
+#' In such cases, the object must be "unquoted" via the `!!` prefix operator.
+#'
+#' @returns An object of class [ggplot2::ggplot].
+#'
+#' @examples
+#' # create [mice::mids] object with [mice::mice()]
+#' imp <- mice::mice(mice::nhanes, print = FALSE)
+#'
+#' # plot moments for all imputed columns
+#' plot_moments(imp)
+#'
+#' # plot trace lines for specific columns by supplying a string or character vector
+#' plot_moments(imp, "chl")
+#' plot_moments(imp, c("chl", "hyp"))
+
+#' # plot trace lines for specific columns by supplying unquoted variable names
+#' plot_moments(imp, chl)
+#' plot_moments(imp, c(chl, hyp))
+#'
+#' # plot trace lines for specific columns by passing an object with variable names
+#' # from the environment, unquoted with `!!`
+#' my_variables <- c("chl", "hyp")
+#' plot_moments(imp, !!my_variables)
+#' # object with variable names must be unquoted with `!!`
+#' try(plot_moments(imp, my_variables))
+#'
+#' @export
+plot_moments <- function(data, vrb = "all") {
+  verify_data(data, imp = TRUE)
+  # # check if any imp
+  # if (is.null(data$chainMean) && is.null(data$chainVar)) {
+  #   cli::cli_abort("No convergence diagnostics found", call. = FALSE)
+  # }
+  vrb <- rlang::enexpr(vrb)
+  vrbs_in_data <- names(data$imp)
+  vrb_matched <- match_vrb(vrb, vrbs_in_data)
+  # extract means and variances
+  means_obs <- colMeans(data$data, na.rm = TRUE)
+  means_imp <- rowMeans(data$chainMean[, data$iteration, ])
+  vars_obs <- apply(data$data, na.rm = TRUE, 2, var)
+  vars_imp <- rowMeans(data$chainVar[, data$iteration, ])
+  available_vrbs <- vrbs_in_data[(!(is.nan(means_imp) | is.na(vars_imp)))]
+  if (any(vrb_matched %nin% available_vrbs)) {
+    cli::cli_inform(
+      c(
+        "Moments plot could not be produced for variable(s):",
+        " " = paste(vrb_matched[which(vrb_matched %nin% available_vrbs)], collapse = ", "),
+        "i" = "No imputed data found."
+      )
+    )
+  }
+  vrb_matched <- vrb_matched[which(vrb_matched %in% available_vrbs)]
+  # create plotting data
+  p <- length(vrb_matched)
+  long <- cbind(
+    data.frame(.vrb = vrb_matched),
+    .mm = c(rep("Means", p), rep("Variances", p)),
+    obs = c(means_obs[vrb_matched], vars_obs[vrb_matched]),
+    imp = c(means_imp[vrb_matched], vars_imp[vrb_matched])
+  )
+  # create plot
+  ggplot2::ggplot(long,
+                  ggplot2::aes(
+                    x = .data$obs,
+                    y = .data$imp
+                  )) +
+    ggplot2::geom_point() +
+    ggplot2::geom_abline(intercept = 0, slope = 1, linetype = "dashed") +
+    ggplot2::facet_wrap(
+      ~ .mm,
+      dir = "v",
+      ncol = 2,
+      scales = "free",
+      strip.position = "top",
+      labeller = function(labels) {
+        labels <- lapply(labels, as.character)
+        list(do.call(paste, c(labels, list(sep = "\n"))))
+      }
+    ) +
+    ggplot2::labs(
+      x = "Observed data",
+      y = "Imputed data",
+    ) +
+    theme_mice() +
+    ggplot2::theme(
+      strip.background = ggplot2::element_blank(),
+      strip.placement = "outside",
+      strip.switch.pad.wrap = ggplot2::unit(0, "cm")
+    )
+}

From 143c7dfb2bdab3311eb606a854ef00ed23fa4f65 Mon Sep 17 00:00:00 2001
From: hanneoberman <h.i.oberman@uu.nl>
Date: Wed, 16 Oct 2024 11:52:09 +0200
Subject: [PATCH 2/2] change variance to SD for scale, and add colors to
 differentiate variables

---
 R/plot_moments.R | 32 ++++++++++++++++----------------
 1 file changed, 16 insertions(+), 16 deletions(-)

diff --git a/R/plot_moments.R b/R/plot_moments.R
index bde33cb..27c0773 100644
--- a/R/plot_moments.R
+++ b/R/plot_moments.R
@@ -48,32 +48,33 @@ plot_moments <- function(data, vrb = "all") {
   # extract means and variances
   means_obs <- colMeans(data$data, na.rm = TRUE)
   means_imp <- rowMeans(data$chainMean[, data$iteration, ])
-  vars_obs <- apply(data$data, na.rm = TRUE, 2, var)
-  vars_imp <- rowMeans(data$chainVar[, data$iteration, ])
-  available_vrbs <- vrbs_in_data[(!(is.nan(means_imp) | is.na(vars_imp)))]
+  sds_obs <- sqrt(apply(data$data, na.rm = TRUE, 2, var))
+  sds_imp <- sqrt(rowMeans(data$chainVar[, data$iteration, ]))
+  # extract relevant variables
+  available_vrbs <- vrbs_in_data[(!(is.nan(means_imp) | is.na(sds_imp)))]
   if (any(vrb_matched %nin% available_vrbs)) {
     cli::cli_inform(
       c(
         "Moments plot could not be produced for variable(s):",
-        " " = paste(vrb_matched[which(vrb_matched %nin% available_vrbs)], collapse = ", "),
-        "i" = "No imputed data found."
-      )
+        " " = paste(vrb_matched[which(vrb_matched %nin% available_vrbs)], collapse = ", ")
+        )
     )
   }
   vrb_matched <- vrb_matched[which(vrb_matched %in% available_vrbs)]
   # create plotting data
   p <- length(vrb_matched)
   long <- cbind(
-    data.frame(.vrb = vrb_matched),
-    .mm = c(rep("Means", p), rep("Variances", p)),
-    obs = c(means_obs[vrb_matched], vars_obs[vrb_matched]),
-    imp = c(means_imp[vrb_matched], vars_imp[vrb_matched])
+    data.frame(vrb = vrb_matched),
+    .mm = c(rep("mean", p), rep("SD", p)),
+    obs = c(means_obs[vrb_matched], sds_obs[vrb_matched]),
+    imp = c(means_imp[vrb_matched], sds_imp[vrb_matched])
   )
   # create plot
   ggplot2::ggplot(long,
                   ggplot2::aes(
                     x = .data$obs,
-                    y = .data$imp
+                    y = .data$imp,
+                    color = .data$vrb
                   )) +
     ggplot2::geom_point() +
     ggplot2::geom_abline(intercept = 0, slope = 1, linetype = "dashed") +
@@ -82,15 +83,14 @@ plot_moments <- function(data, vrb = "all") {
       dir = "v",
       ncol = 2,
       scales = "free",
-      strip.position = "top",
-      labeller = function(labels) {
-        labels <- lapply(labels, as.character)
-        list(do.call(paste, c(labels, list(sep = "\n"))))
-      }
+      labeller = ggplot2::as_labeller(
+        c(mean = "mean", SD = "SD")),
+      strip.position = "top"
     ) +
     ggplot2::labs(
       x = "Observed data",
       y = "Imputed data",
+      color = ""
     ) +
     theme_mice() +
     ggplot2::theme(