diff --git a/DESCRIPTION b/DESCRIPTION
index 39077d11..ed5736b0 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -9,7 +9,8 @@ Authors@R: c(
     person("Thom", "Volker", role = "ctb", comment = c(ORCID = "0000-0002-2408-7820")),
     person("Gerko", "Vink", role = "ctb", comment = c(ORCID = "0000-0001-9767-1924")),
     person("Pepijn", "Vink", role = "ctb", comment = c(ORCID = "0000-0001-6960-9904")),
-    person("Jamie", "Wallis", role = "ctb", comment = c(ORCID = "0000-0003-2765-3813"))
+    person("Jamie", "Wallis", role = "ctb", comment = c(ORCID = "0000-0003-2765-3813")),
+    person("Kyle", "Lang", role = "ctb", comment = c(ORCID = "0000-0001-5340-7849"))
     )
 Description: Enhance a 'mice' imputation workflow with visualizations for
     incomplete and/or imputed data. The plotting functions produce
@@ -46,4 +47,4 @@ Config/testthat/edition: 3
 Copyright: 'ggmice' authors
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2
diff --git a/NEWS.md b/NEWS.md
index ef10f9d5..1e0b2721 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,7 +2,8 @@
 
 ## Bug fixes
 
-* Correct labeling of 'exclusion-restriction' variables in `plot_pred()` (#128) 
+* Correct labeling of 'exclusion-restriction' variables in `plot_pred()` (#128)
+* Parsing of `vrb` argument in all `plot_*()` functions: variable name(s) from object in global environment now recognized using `!!` notation (#157)
 
 ## Minor changes
 
diff --git a/R/ggmice.R b/R/ggmice.R
index 3ab1862e..d2e47336 100644
--- a/R/ggmice.R
+++ b/R/ggmice.R
@@ -60,8 +60,7 @@ ggmice <- function(data = NULL,
   }
   if (length(vrbs) > length(unique(vrbs))) {
     cli::cli_abort(
-      c("The data must have unique column names.",
-        "x" = "Duplication found in {vrbs[duplicated(vrbs)]}")
+      c("The data must have unique column names.", "x" = "Duplication found in {vrbs[duplicated(vrbs)]}")
     )
   }
   # extract mapping variables
@@ -107,8 +106,8 @@ ggmice <- function(data = NULL,
           .imp = 0,
           .id = rownames(data$data),
           data$data
-        )[!miss_xy,],
-        data.frame(.where = "imputed", mice::complete(data, action = "long"))[where_xy,]
+        )[!miss_xy, ],
+        data.frame(.where = "imputed", mice::complete(data, action = "long"))[where_xy, ]
       ),
       .where = factor(
         .where,
@@ -154,7 +153,6 @@ ggmice <- function(data = NULL,
   return(gg)
 }
 
-
 #' Utils function to extract mapping variables
 #'
 #' @param data Incomplete dataset or mids object.
@@ -197,11 +195,9 @@ match_mapping <- function(data, vrbs, mapping_in) {
         inherits(try(dplyr::mutate(mapping_data,
                                    !!rlang::parse_quo(mapping_text, env = rlang::current_env())),
                      silent = TRUE)
-                 ,
-                 "try-error")) {
+                 , "try-error")) {
       cli::cli_abort(
-        c("Must provide a valid mapping variable.",
-          "x" = "Mapping variable '{mapping_text}' not found in the data or imputations.")
+        c("Must provide a valid mapping variable.", "x" = "Mapping variable '{mapping_text}' not found in the data or imputations.")
       )
     } else {
       cli::cli_warn(
diff --git a/R/plot_corr.R b/R/plot_corr.R
index 29f7d957..2d290e04 100644
--- a/R/plot_corr.R
+++ b/R/plot_corr.R
@@ -11,7 +11,22 @@
 #' @return An object of class [ggplot2::ggplot].
 #'
 #' @examples
-#' plot_corr(mice::nhanes, label = TRUE)
+#' # plot correlations for all columns
+#' plot_corr(mice::nhanes)
+#'
+#' # plot correlations for specific columns by supplying a character vector
+#' plot_corr(mice::nhanes, c("chl", "hyp"))
+#'
+#' # plot correlations for specific columns by supplying unquoted variable names
+#' plot_corr(mice::nhanes, c(chl, hyp))
+#'
+#' # plot correlations for specific columns by passing an object with variable names
+#' # from the environment, unquoted with `!!`
+#' my_variables <- c("chl", "hyp")
+#' plot_corr(mice::nhanes, !!my_variables)
+#' # object with variable names must be unquoted with `!!`
+#' try(plot_corr(mice::nhanes, my_variables))
+#'
 #' @export
 plot_corr <-
   function(data,
@@ -25,38 +40,33 @@ plot_corr <-
       data <- as.data.frame(data)
     }
     verify_data(data = data, df = TRUE)
-    vrb <- substitute(vrb)
-    if (vrb != "all" && length(vrb) < 2) {
+    vrb <- rlang::enexpr(vrb)
+    vrb_matched <- match_vrb(vrb, names(data))
+    if (length(vrb_matched) < 2) {
       cli::cli_abort("The number of variables should be two or more to compute correlations.")
     }
-    if (vrb[1] == "all") {
-      vrb <- names(data)
-    } else {
-      data <- dplyr::select(data, {{vrb}})
-      vrb <- names(data)
-    }
     # check if any column is constant
-    constants <- apply(data, MARGIN = 2, function(x) {
+    constants <- apply(data[, vrb_matched], MARGIN = 2, function(x) {
       all(is.na(x)) || max(x, na.rm = TRUE) == min(x, na.rm = TRUE)
     })
     if (any(constants)) {
-      vrb <- names(data[, !constants])
+      vrb_matched <- vrb_matched[!constants]
       cli::cli_inform(
         c(
           "No correlations computed for variable(s):",
           " " = paste(names(constants[which(constants)]), collapse = ", "),
-          "x" = "Correlation undefined for constants."
+          "i" = "Correlations are undefined for constants."
         )
       )
     }
-
-    p <- length(vrb)
+    # compute correlations
+    p <- length(vrb_matched)
     corrs <- data.frame(
-      vrb = rep(vrb, each = p),
-      prd = vrb,
+      vrb = rep(vrb_matched, each = p),
+      prd = vrb_matched,
       corr = matrix(
         round(stats::cov2cor(
-          stats::cov(data.matrix(data[, vrb]), use = "pairwise.complete.obs")
+          stats::cov(data.matrix(data[, vrb_matched]), use = "pairwise.complete.obs")
         ), 2),
         nrow = p * p,
         byrow = TRUE
@@ -65,6 +75,7 @@ plot_corr <-
     if (!diagonal) {
       corrs[corrs$vrb == corrs$prd, "corr"] <- NA
     }
+    # create plot
     gg <-
       ggplot2::ggplot(corrs,
                       ggplot2::aes(
@@ -74,8 +85,8 @@ plot_corr <-
                         fill = .data$corr
                       )) +
       ggplot2::geom_tile(color = "black", alpha = 0.6) +
-      ggplot2::scale_x_discrete(limits = vrb, position = "top") +
-      ggplot2::scale_y_discrete(limits = rev(vrb)) +
+      ggplot2::scale_x_discrete(limits = vrb_matched, position = "top") +
+      ggplot2::scale_y_discrete(limits = rev(vrb_matched)) +
       ggplot2::scale_fill_gradient2(
         low = ggplot2::alpha("deepskyblue", 0.6),
         mid = "lightyellow",
@@ -91,13 +102,11 @@ plot_corr <-
           y = "Variable to impute",
           fill = "Correlation*
       ",
-      caption = "*pairwise complete observations"
+          caption = "*pairwise complete observations"
         )
     } else {
       gg <- gg +
-        ggplot2::labs(x = "Imputation model predictor",
-                      y = "Variable to impute",
-                      fill = "Correlation")
+        ggplot2::labs(x = "Imputation model predictor", y = "Variable to impute", fill = "Correlation")
     }
     if (label) {
       gg <-
diff --git a/R/plot_flux.R b/R/plot_flux.R
index 8f110f41..a3cb5b0b 100644
--- a/R/plot_flux.R
+++ b/R/plot_flux.R
@@ -8,7 +8,22 @@
 #' @return An object of class [ggplot2::ggplot].
 #'
 #' @examples
+#' # plot flux for all columns
 #' plot_flux(mice::nhanes)
+#'
+#' # plot flux for specific columns by supplying a character vector
+#' plot_flux(mice::nhanes, c("chl", "hyp"))
+#'
+#' # plot flux for specific columns by supplying unquoted variable names
+#' plot_flux(mice::nhanes, c(chl, hyp))
+#'
+#' # plot flux for specific columns by passing an object with variable names
+#' # from the environment, unquoted with `!!`
+#' my_variables <- c("chl", "hyp")
+#' plot_flux(mice::nhanes, !!my_variables)
+#' # object with variable names must be unquoted with `!!`
+#' try(plot_flux(mice::nhanes, my_variables))
+#'
 #' @export
 plot_flux <-
   function(data,
@@ -16,17 +31,14 @@ plot_flux <-
            label = TRUE,
            caption = TRUE) {
     verify_data(data, df = TRUE)
-    vrb <- substitute(vrb)
-    if (vrb != "all" && length(vrb) < 2) {
+    vrb <- rlang::enexpr(vrb)
+    vrb_matched <- match_vrb(vrb, names(data))
+    if (length(vrb_matched) < 2) {
       cli::cli_abort("The number of variables should be two or more to compute flux.")
     }
-    if (vrb[1] == "all") {
-      vrb <- names(data)
-    } else {
-      vrb <- names(dplyr::select(data, {{vrb}}))
-    }
-    # plot in and outflux
-    flx <- mice::flux(data[, vrb])[, c("influx", "outflux")]
+    # compute flux
+    flx <- mice::flux(data[, vrb_matched])[, c("influx", "outflux")]
+    # create plot
     gg <-
       data.frame(
         vrb = rownames(flx),
diff --git a/R/plot_pattern.R b/R/plot_pattern.R
index 06342e6c..ed8d9192 100644
--- a/R/plot_pattern.R
+++ b/R/plot_pattern.R
@@ -11,7 +11,22 @@
 #' @return An object of class [ggplot2::ggplot].
 #'
 #' @examples
+#' # plot missing data pattern for all columns
 #' plot_pattern(mice::nhanes)
+#'
+#' # plot missing data pattern for specific columns by supplying a character vector
+#' plot_pattern(mice::nhanes, c("chl", "hyp"))
+#'
+#' # plot missing data pattern for specific columns by supplying unquoted variable names
+#' plot_pattern(mice::nhanes, c(chl, hyp))
+#'
+#' # plot missing data pattern for specific columns by passing an object with variable names
+#' # from the environment, unquoted with `!!`
+#' my_variables <- c("chl", "hyp")
+#' plot_pattern(mice::nhanes, !!my_variables)
+#' # object with variable names must be unquoted with `!!`
+#' try(plot_pattern(mice::nhanes, my_variables))
+#'
 #' @export
 plot_pattern <-
   function(data,
@@ -21,21 +36,16 @@ plot_pattern <-
            cluster = NULL,
            npat = NULL,
            caption = TRUE) {
-    # input processing
     if (is.matrix(data) && ncol(data) > 1) {
       data <- as.data.frame(data)
     }
     verify_data(data, df = TRUE)
-    vrb <- substitute(vrb)
-    if (vrb != "all" && length(vrb) < 2) {
+    vrb <- rlang::enexpr(vrb)
+    vrb_matched <- match_vrb(vrb, names(data))
+    if (length(vrb_matched) < 2) {
       cli::cli_abort("The number of variables should be two or more to compute missing data patterns.")
     }
-    if (vrb[1] == "all") {
-      vrb <- names(data)
-    } else {
-      vrb <- names(dplyr::select(as.data.frame(data), {{vrb}}))
-    }
-    if (".x" %in% vrb || ".y" %in% vrb) {
+    if (".x" %in% vrb_matched || ".y" %in% vrb_matched) {
       cli::cli_abort(
         c(
           "The variable names '.x' and '.y' are used internally to produce the missing data pattern plot.",
@@ -44,7 +54,7 @@ plot_pattern <-
       )
     }
     if (!is.null(cluster)) {
-      if (cluster %nin% names(data[, vrb])) {
+      if (cluster %nin% names(data[, vrb_matched])) {
         cli::cli_abort(
           c("Cluster variable not recognized.",
             "i" = "Please provide the variable name as a character string.")
@@ -61,7 +71,7 @@ plot_pattern <-
     }
 
     # get missing data pattern
-    pat <- mice::md.pattern(data[, vrb], plot = FALSE)
+    pat <- mice::md.pattern(data[, vrb_matched], plot = FALSE)
     rows_pat_full <-
       (nrow(pat) - 1) # full number of missing data patterns
 
diff --git a/R/plot_pred.R b/R/plot_pred.R
index f1484a87..0fb8b7c9 100644
--- a/R/plot_pred.R
+++ b/R/plot_pred.R
@@ -10,8 +10,25 @@
 #' @return An object of class `ggplot2::ggplot`.
 #'
 #' @examples
+#' # generate a predictor matrix
 #' pred <- mice::quickpred(mice::nhanes)
+#'
+#' # plot predictor matrix for all columns
 #' plot_pred(pred)
+#'
+#' # plot predictor matrix for specific columns by supplying a character vector
+#' plot_pred(pred, c("chl", "hyp"))
+#'
+#' # plot predictor matrix for specific columns by supplying unquoted variable names
+#' plot_pred(pred, c(chl, hyp))
+#'
+#' # plot predictor matrix for specific columns by passing an object with variable names
+#' # from the environment, unquoted with `!!`
+#' my_variables <- c("chl", "hyp")
+#' plot_pred(pred, !!my_variables)
+#' # object with variable names must be unquoted with `!!`
+#' try(plot_pred(pred, my_variables))
+#'
 #' @export
 plot_pred <-
   function(data,
@@ -21,7 +38,9 @@ plot_pred <-
            square = TRUE,
            rotate = FALSE) {
     verify_data(data, pred = TRUE)
-    p <- nrow(data)
+    vrb <- rlang::enexpr(vrb)
+    vrb_matched <- match_vrb(vrb, row.names(data))
+    p <- length(vrb_matched)
     if (!is.null(method) && is.character(method)) {
       if (length(method) == 1) {
         method <- rep(method, p)
@@ -37,17 +56,10 @@ plot_pred <-
     if (!is.character(method) || length(method) != p) {
       cli::cli_abort("Method should be NULL or a character string or vector (of length 1 or `ncol(data)`).")
     }
-    vrb <- substitute(vrb)
-    if (vrb[1] == "all") {
-      vrb <- names(data)
-    } else {
-      vrb <- names(dplyr::select(as.data.frame(data), {{vrb}}))
-    }
-    vrbs <- row.names(data)
     long <- data.frame(
       vrb = 1:p,
-      prd = rep(vrbs, each = p),
-      ind = matrix(data, nrow = p * p, byrow = TRUE)
+      prd = rep(vrb_matched, each = p),
+      ind = matrix(data[vrb_matched, vrb_matched], nrow = p * p, byrow = TRUE)
     ) %>% dplyr::mutate(clr = factor(
       .data$ind,
       levels = c(-3, -2, 0, 1, 2),
@@ -70,10 +82,10 @@ plot_pred <-
                         fill = .data$clr
                       )) +
       ggplot2::geom_tile(color = "black", alpha = 0.6) +
-      ggplot2::scale_x_discrete(limits = vrbs, position = "top") +
+      ggplot2::scale_x_discrete(limits = vrb_matched, position = "top") +
       ggplot2::scale_y_reverse(
         breaks = 1:p,
-        labels = vrbs,
+        labels = vrb_matched,
         sec.axis = ggplot2::dup_axis(labels = method, name = ylabel)
       ) +
       ggplot2::scale_fill_manual(
diff --git a/R/plot_trace.R b/R/plot_trace.R
index ec8f2580..ecc6c57f 100644
--- a/R/plot_trace.R
+++ b/R/plot_trace.R
@@ -1,65 +1,81 @@
 #' Plot the trace lines of the imputation algorithm
 #'
 #' @param data An object of class [mice::mids].
-#' @param vrb String, vector, or unquoted expression with variable name(s), default is "all".
+#' @param vrb String, vector, or unquoted expression with variable name(s),
+#'   default is "all".
 #'
-#' @return An object of class [ggplot2::ggplot].
+#' @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 trace lines for all imputed columns
 #' plot_trace(imp)
+#'
+#' # plot trace lines for specific columns by supplying a string or character vector
+#' plot_trace(imp, "chl")
+#' plot_trace(imp, c("chl", "hyp"))
+
+#' # plot trace lines for specific columns by supplying unquoted variable names
+#' plot_trace(imp, chl)
+#' plot_trace(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_trace(imp, !!my_variables)
+#' # object with variable names must be unquoted with `!!`
+#' try(plot_trace(imp, my_variables))
+#'
 #' @export
 plot_trace <- function(data, vrb = "all") {
   verify_data(data, imp = TRUE)
   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$imp)
+  vrb_matched <- match_vrb(vrb, vrbs_in_data)
   # extract chain means and chain standard deviations
   mn <- data$chainMean
   sm <- sqrt(data$chainVar)
-
-  # select variable to plot from list of imputed variables
-  vrb <- substitute(vrb)
-  varlist <-
-    names(data$imp)[apply(!(is.nan(mn) | is.na(mn)), 1, all)]
-  if (as.character(vrb)[1] == "all") {
-    vrb <- varlist
-  } else {
-    vrb <- names(dplyr::select(data$data, {{vrb}}))
-  }
-  if (any(vrb %nin% varlist)) {
+  available_vrbs <- vrbs_in_data[apply(!(is.nan(mn) | is.na(sm)), 1, all)]
+  if (any(vrb_matched %nin% available_vrbs)) {
     cli::cli_inform(
       c(
         "Trace plot could not be produced for variable(s):",
-        " " = paste(vrb[which(vrb %nin% varlist)], collapse = ", "),
-        "x" = "No convergence diagnostics found."
+        " " = paste(vrb_matched[which(vrb_matched %nin% available_vrbs)], collapse = ", "),
+        "i" = "No convergence diagnostics found."
       )
     )
-    if (any(vrb %in% varlist)) {
-      vrb <- vrb[which(vrb %in% varlist)]
-    } else {
-      cli::cli_abort(c("x" = "None of the variables are imputed.",
-                       "No plots can be produced."))
-    }
   }
-
-  p <- length(vrb)
+  vrb_matched <- vrb_matched[which(vrb_matched %in% available_vrbs)]
+  # compute diagnostics
+  p <- length(vrb_matched)
   m <- data$m
   it <- data$iteration
-  long <- cbind(expand.grid(.it = seq_len(it), .m = seq_len(m)),
-                data.frame(
-                  .ms = rep(c("mean", "sd"), each = m * it * p),
-                  vrb = rep(vrb, each = m * it, times = 2),
-                  val = c(matrix(aperm(mn[vrb, , , drop = FALSE], c(
-                    2, 3, 1
-                  )), nrow = m * it * p),
-                  matrix(aperm(sm[vrb, , , drop = FALSE], c(
-                    2, 3, 1
-                  )), nrow = m * it * p))
-                ))
-
-  # plot the convergence diagnostics
+  long <- cbind(
+    expand.grid(.it = seq_len(it), .m = seq_len(m)),
+    data.frame(
+      .ms = rep(c("mean", "sd"), each = m * it * p),
+      vrb_matched = rep(vrb_matched, each = m * it, times = 2),
+      val = c(
+        matrix(aperm(mn[vrb_matched, , , drop = FALSE], c(
+          2, 3, 1)), nrow = m * it * p),
+        matrix(aperm(sm[vrb_matched, , , drop = FALSE], c(
+          2, 3, 1)), nrow = m * it * p)
+        )
+    )
+  )
+  # create plot
   ggplot2::ggplot(long,
                   ggplot2::aes(
                     x = .data$.it,
@@ -69,7 +85,7 @@ plot_trace <- function(data, vrb = "all") {
     ggplot2::geom_line(linewidth = 0.6) +
     ggplot2::geom_hline(yintercept = -Inf) +
     ggplot2::facet_wrap(
-      .ms ~ vrb,
+      .ms ~ vrb_matched,
       dir = "v",
       ncol = 2,
       scales = "free_y",
@@ -79,9 +95,7 @@ plot_trace <- function(data, vrb = "all") {
         list(do.call(paste, c(labels, list(sep = "\n"))))
       }
     ) +
-    ggplot2::labs(x = "Iteration",
-                  y = "Imputation parameter",
-                  color = "Imputation number") +
+    ggplot2::labs(x = "Iteration", y = "Imputation parameter", color = "Imputation number") +
     theme_mice() +
     ggplot2::theme(
       strip.background = ggplot2::element_blank(),
diff --git a/R/utils.R b/R/utils.R
index 2cb42595..89b62d89 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -100,5 +100,39 @@ verify_data <- function(data,
   }
 }
 
+#' Utils function to match `vrb` argument to variable names in `data`
+#'
+#' @param vrb The input supplied to the 'vrb' argument.
+#' @param vrbs_in_data A character vector of available variable names in `data`.
+#'
+#' @return String or character vector with matched variable name(s).
+#'
+#' @keywords internal
+#' @noRd
+match_vrb <- function(vrb, vrbs_in_data) {
+  if (is.call(vrb))
+    vrb <- as.character(vrb)[-1]
+  if (is.symbol(vrb))
+    vrb <- as.character(vrb)
+  if (length(vrb) == 1 && as.character(vrb) == "all") {
+    vrb <- vrbs_in_data
+  }
+  if (all(vrb %nin% vrbs_in_data)) {
+    cli::cli_abort(
+      c(
+        "x" = "The variable name(s) supplied to {.var vrb} could not be found in {.var data}.",
+        "i" = "If you supply an object with variable names from the environment, use `!!` to unqote:",
+        " " = paste0("{.code vrb = !!", vrb, "}")
+      )
+    )
+  }
+  if (any(vrb %nin% vrbs_in_data)) {
+    cli::cli_warn(c("x" = "The following variables are not present in {.var data}:", " " = paste(
+      setdiff(vrb, vrbs_in_data), collapse = ", "
+    )))
+  }
+  return(vrb)
+}
+
 # suppress undefined global functions or variables note
 utils::globalVariables(c(".id", ".imp", ".where", ".id", "where", "name", "value"))
diff --git a/man/plot_corr.Rd b/man/plot_corr.Rd
index fa57995d..a12af753 100644
--- a/man/plot_corr.Rd
+++ b/man/plot_corr.Rd
@@ -36,5 +36,20 @@ An object of class \link[ggplot2:ggplot]{ggplot2::ggplot}.
 Plot correlations between (incomplete) variables
 }
 \examples{
-plot_corr(mice::nhanes, label = TRUE)
+# plot correlations for all columns
+plot_corr(mice::nhanes)
+
+# plot correlations for specific columns by supplying a character vector
+plot_corr(mice::nhanes, c("chl", "hyp"))
+
+# plot correlations for specific columns by supplying unquoted variable names
+plot_corr(mice::nhanes, c(chl, hyp))
+
+# plot correlations for specific columns by passing an object with variable names
+# from the environment, unquoted with `!!`
+my_variables <- c("chl", "hyp")
+plot_corr(mice::nhanes, !!my_variables)
+# object with variable names must be unquoted with `!!`
+try(plot_corr(mice::nhanes, my_variables))
+
 }
diff --git a/man/plot_flux.Rd b/man/plot_flux.Rd
index 7bea22c5..6a274b23 100644
--- a/man/plot_flux.Rd
+++ b/man/plot_flux.Rd
@@ -22,5 +22,20 @@ An object of class \link[ggplot2:ggplot]{ggplot2::ggplot}.
 Plot the influx and outflux of a multivariate missing data pattern
 }
 \examples{
+# plot flux for all columns
 plot_flux(mice::nhanes)
+
+# plot flux for specific columns by supplying a character vector
+plot_flux(mice::nhanes, c("chl", "hyp"))
+
+# plot flux for specific columns by supplying unquoted variable names
+plot_flux(mice::nhanes, c(chl, hyp))
+
+# plot flux for specific columns by passing an object with variable names
+# from the environment, unquoted with `!!`
+my_variables <- c("chl", "hyp")
+plot_flux(mice::nhanes, !!my_variables)
+# object with variable names must be unquoted with `!!`
+try(plot_flux(mice::nhanes, my_variables))
+
 }
diff --git a/man/plot_pattern.Rd b/man/plot_pattern.Rd
index 3d27a04a..f964c99d 100644
--- a/man/plot_pattern.Rd
+++ b/man/plot_pattern.Rd
@@ -36,5 +36,20 @@ An object of class \link[ggplot2:ggplot]{ggplot2::ggplot}.
 Plot the missing data pattern of an incomplete dataset
 }
 \examples{
+# plot missing data pattern for all columns
 plot_pattern(mice::nhanes)
+
+# plot missing data pattern for specific columns by supplying a character vector
+plot_pattern(mice::nhanes, c("chl", "hyp"))
+
+# plot missing data pattern for specific columns by supplying unquoted variable names
+plot_pattern(mice::nhanes, c(chl, hyp))
+
+# plot missing data pattern for specific columns by passing an object with variable names
+# from the environment, unquoted with `!!`
+my_variables <- c("chl", "hyp")
+plot_pattern(mice::nhanes, !!my_variables)
+# object with variable names must be unquoted with `!!`
+try(plot_pattern(mice::nhanes, my_variables))
+
 }
diff --git a/man/plot_pred.Rd b/man/plot_pred.Rd
index c71970a6..2e3ee6f3 100644
--- a/man/plot_pred.Rd
+++ b/man/plot_pred.Rd
@@ -33,6 +33,23 @@ An object of class \code{ggplot2::ggplot}.
 Plot the predictor matrix of an imputation model
 }
 \examples{
+# generate a predictor matrix
 pred <- mice::quickpred(mice::nhanes)
+
+# plot predictor matrix for all columns
 plot_pred(pred)
+
+# plot predictor matrix for specific columns by supplying a character vector
+plot_pred(pred, c("chl", "hyp"))
+
+# plot predictor matrix for specific columns by supplying unquoted variable names
+plot_pred(pred, c(chl, hyp))
+
+# plot predictor matrix for specific columns by passing an object with variable names
+# from the environment, unquoted with `!!`
+my_variables <- c("chl", "hyp")
+plot_pred(pred, !!my_variables)
+# object with variable names must be unquoted with `!!`
+try(plot_pred(pred, my_variables))
+
 }
diff --git a/man/plot_trace.Rd b/man/plot_trace.Rd
index acb4cf34..cc939820 100644
--- a/man/plot_trace.Rd
+++ b/man/plot_trace.Rd
@@ -9,7 +9,8 @@ plot_trace(data, vrb = "all")
 \arguments{
 \item{data}{An object of class \link[mice:mids-class]{mice::mids}.}
 
-\item{vrb}{String, vector, or unquoted expression with variable name(s), default is "all".}
+\item{vrb}{String, vector, or unquoted expression with variable name(s),
+default is "all".}
 }
 \value{
 An object of class \link[ggplot2:ggplot]{ggplot2::ggplot}.
@@ -17,7 +18,32 @@ An object of class \link[ggplot2:ggplot]{ggplot2::ggplot}.
 \description{
 Plot the trace lines of the imputation algorithm
 }
+\details{
+The \code{vrb} argument is "quoted" via \code{\link[rlang:defusing-advanced]{rlang::enexpr()}} and evaluated according
+to \href{https://adv-r.hadley.nz/metaprogramming.html}{tidy evaluation principles}.
+In practice, this technical nuance only affects users when passing an object
+from the environment (e.g., a vector of variable names) to the \code{vrb} argument.
+In such cases, the object must be "unquoted" via the \verb{!!} prefix operator.
+}
 \examples{
+# create [mice::mids] object with [mice::mice()]
 imp <- mice::mice(mice::nhanes, print = FALSE)
+
+# plot trace lines for all imputed columns
 plot_trace(imp)
+
+# plot trace lines for specific columns by supplying a string or character vector
+plot_trace(imp, "chl")
+plot_trace(imp, c("chl", "hyp"))
+# plot trace lines for specific columns by supplying unquoted variable names
+plot_trace(imp, chl)
+plot_trace(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_trace(imp, !!my_variables)
+# object with variable names must be unquoted with `!!`
+try(plot_trace(imp, my_variables))
+
 }
diff --git a/tests/testthat/test-plot_trace.R b/tests/testthat/test-plot_trace.R
index ff18805d..e294ebcb 100644
--- a/tests/testthat/test-plot_trace.R
+++ b/tests/testthat/test-plot_trace.R
@@ -1,6 +1,7 @@
 # create test objects
 dat <- mice::nhanes
 imp <- mice::mice(dat, printFlag = FALSE)
+v <- c("bmi", "hyp")
 
 # tests
 test_that("plot_trace creates ggplot object", {
@@ -11,6 +12,8 @@ test_that("plot_trace creates ggplot object", {
   expect_s3_class(plot_trace(imp, vrb = bmi), "ggplot")
   expect_s3_class(plot_trace(imp, vrb = c("bmi", "hyp")), "ggplot")
   expect_s3_class(plot_trace(imp, vrb = c(bmi, hyp)), "ggplot")
+  expect_s3_class(plot_trace(imp, vrb = !!v), "ggplot")
+  expect_s3_class(plot_trace(imp, vrb = !!v[1]), "ggplot")
 })
 
 test_that("plot_trace returns error with incorrect argument(s)", {
@@ -18,4 +21,6 @@ test_that("plot_trace returns error with incorrect argument(s)", {
   expect_error(plot_trace(imp, vrb = "test"))
   expect_error(plot_trace(imp, vrb = "age"))
   expect_message(plot_trace(imp, vrb = c("age", "bmi")))
+  expect_error(plot_trace(imp, vrb = v))
+  expect_error(plot_trace(imp, vrb = v[1]))
 })