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Plotting Likert-type items

Source: R/gglikert.R
gglikert.Rd

Combines several factor variables using the same list of ordered levels (e.g. Likert-type scales) into a unique data frame and generates a centered bar plot.

Usage

gglikert(
  data,
  include = dplyr::everything(),
  weights = NULL,
  y = ".question",
  variable_labels = NULL,
  sort = c("none", "ascending", "descending"),
  sort_method = c("prop", "prop_lower", "mean", "median"),
  sort_prop_include_center = totals_include_center,
  factor_to_sort = ".question",
  exclude_fill_values = NULL,
  cutoff = NULL,
  data_fun = NULL,
  add_labels = TRUE,
  labels_size = 3.5,
  labels_color = "auto",
  labels_accuracy = 1,
  labels_hide_below = 0.05,
  add_totals = TRUE,
  totals_size = labels_size,
  totals_color = "black",
  totals_accuracy = labels_accuracy,
  totals_fontface = "bold",
  totals_include_center = FALSE,
  totals_hjust = 0.1,
  y_reverse = TRUE,
  y_label_wrap = 50,
  reverse_likert = FALSE,
  width = 0.9,
  facet_rows = NULL,
  facet_cols = NULL,
  facet_label_wrap = 50,
  symmetric = FALSE
)

gglikert_data(
  data,
  include = dplyr::everything(),
  weights = NULL,
  variable_labels = NULL,
  sort = c("none", "ascending", "descending"),
  sort_method = c("prop", "prop_lower", "mean", "median"),
  sort_prop_include_center = TRUE,
  factor_to_sort = ".question",
  exclude_fill_values = NULL,
  cutoff = NULL,
  data_fun = NULL
)

gglikert_stacked(
  data,
  include = dplyr::everything(),
  weights = NULL,
  y = ".question",
  variable_labels = NULL,
  sort = c("none", "ascending", "descending"),
  sort_method = c("prop", "prop_lower", "mean", "median"),
  sort_prop_include_center = FALSE,
  factor_to_sort = ".question",
  data_fun = NULL,
  add_labels = TRUE,
  labels_size = 3.5,
  labels_color = "auto",
  labels_accuracy = 1,
  labels_hide_below = 0.05,
  add_median_line = FALSE,
  y_reverse = TRUE,
  y_label_wrap = 50,
  reverse_fill = TRUE,
  width = 0.9
)

Arguments

data

a data frame

include

variables to include, accepts tidy-select syntax

weights

optional variable name of a weighting variable, accepts tidy-select syntax

y

name of the variable to be plotted on y axis (relevant when .question is mapped to "facets, see examples), accepts tidy-select syntax

variable_labels

a named list or a named vector of custom variable labels

sort

should the factor defined by factor_to_sort be sorted according to the answers (see sort_method)? One of "none" (default), "ascending" or "descending"

sort_method

method used to sort the variables: "prop" sort according to the proportion of answers higher than the centered level, "prop_lower" according to the proportion lower than the centered level, "mean" considers answer as a score and sort according to the mean score, "median" used the median and the majority judgment rule for tie-breaking.

sort_prop_include_center

when sorting with "prop" and if the number of levels is uneven, should half of the central level be taken into account to compute the proportion?

factor_to_sort

name of the factor column to sort if sort is not equal to "none"; by default the list of questions passed to include; should be one factor column of the tibble returned by gglikert_data(); accepts tidy-select syntax

exclude_fill_values

Vector of values that should not be displayed (but still taken into account for computing proportions), see position_likert()

cutoff

number of categories to be displayed negatively (i.e. on the left of the x axis or the bottom of the y axis), could be a decimal value: 2 to display negatively the two first categories, 2.5 to display negatively the two first categories and half of the third, 2.2 to display negatively the two first categories and a fifth of the third (see examples). By default (NULL), it will be equal to the number of categories divided by 2, i.e. it will be centered.

data_fun

for advanced usage, custom function to be applied to the generated dataset at the end of gglikert_data()

add_labels

should percentage labels be added to the plot?

labels_size

size of the percentage labels

labels_color

color of the percentage labels ("auto" to use hex_bw() to determine a font color based on background color)

labels_accuracy

accuracy of the percentages, see scales::label_percent()

labels_hide_below

if provided, values below will be masked, see label_percent_abs()

add_totals

should the total proportions of negative and positive answers be added to plot? This option is not compatible with facets!

totals_size

size of the total proportions

totals_color

color of the total proportions

totals_accuracy

accuracy of the total proportions, see scales::label_percent()

totals_fontface

font face of the total proportions

totals_include_center

if the number of levels is uneven, should half of the center level be added to the total proportions?

totals_hjust

horizontal adjustment of totals labels on the x axis

y_reverse

should the y axis be reversed?

y_label_wrap

number of characters per line for y axis labels, see scales::label_wrap()

reverse_likert

if TRUE, will reverse the default stacking order, see position_likert()

width

bar width, see ggplot2::geom_bar()

facet_rows, facet_cols

A set of variables or expressions quoted by ggplot2::vars() and defining faceting groups on the rows or columns dimension (see examples)

facet_label_wrap

number of characters per line for facet labels, see ggplot2::label_wrap_gen()

symmetric

should the x-axis be symmetric?

add_median_line

add a vertical line at 50%?

reverse_fill

if TRUE, will reverse the default stacking order, see ggplot2::position_fill()

Value

A ggplot2 plot or a tibble.

Details

You could use gglikert_data() to just produce the dataset to be plotted.

If variable labels have been defined (see labelled::var_label()), they will be considered. You can also pass custom variables labels with the variable_labels argument.

See also

vignette("gglikert"), position_likert(), stat_prop()

Examples

library(ggplot2)
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

likert_levels <- c(
  "Strongly disagree",
  "Disagree",
  "Neither agree nor disagree",
  "Agree",
  "Strongly agree"
)
set.seed(42)
df <-
  tibble(
    q1 = sample(likert_levels, 150, replace = TRUE),
    q2 = sample(likert_levels, 150, replace = TRUE, prob = 5:1),
    q3 = sample(likert_levels, 150, replace = TRUE, prob = 1:5),
    q4 = sample(likert_levels, 150, replace = TRUE, prob = 1:5),
    q5 = sample(c(likert_levels, NA), 150, replace = TRUE),
    q6 = sample(likert_levels, 150, replace = TRUE, prob = c(1, 0, 1, 1, 0))
  ) |>
  mutate(across(everything(), ~ factor(.x, levels = likert_levels)))

gglikert(df)


gglikert(df, include = q1:3) +
  scale_fill_likert(pal = scales::brewer_pal(palette = "PRGn"))
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.


gglikert(df, sort = "ascending")


# \donttest{
gglikert(df, sort = "ascending", sort_prop_include_center = TRUE)


gglikert(df, sort = "ascending", sort_method = "mean")


gglikert(df, reverse_likert = TRUE)


gglikert(df, add_totals = FALSE, add_labels = FALSE)


gglikert(
  df,
  totals_include_center = TRUE,
  totals_hjust = .25,
  totals_size = 4.5,
  totals_fontface = "italic",
  totals_accuracy = .01,
  labels_accuracy = 1,
  labels_size = 2.5,
  labels_hide_below = .25
)


gglikert(df, exclude_fill_values = "Neither agree nor disagree")


if (require("labelled")) {
  df |>
    set_variable_labels(
      q1 = "First question",
      q2 = "Second question"
    ) |>
    gglikert(
      variable_labels = c(
        q4 = "a custom label",
        q6 = "a very very very very very very very very very very long label"
      ),
      y_label_wrap = 25
    )
}
#> Loading required package: labelled


# Facets
df_group <- df
df_group$group <- sample(c("A", "B"), 150, replace = TRUE)

gglikert(df_group, q1:q6, facet_rows = vars(group))


gglikert(df_group, q1:q6, facet_cols = vars(group))


gglikert(df_group, q1:q6, y = "group", facet_rows = vars(.question))


# Custom function to be applied on data
f <- function(d) {
  d$.question <- forcats::fct_relevel(d$.question, "q5", "q2")
  d
}
gglikert(df, include = q1:q6, data_fun = f)


# Custom center
gglikert(df, cutoff = 2)


gglikert(df, cutoff = 1)


gglikert(df, cutoff = 1, symmetric = TRUE)


# }
gglikert_stacked(df, q1:q6)


gglikert_stacked(df, q1:q6, add_median_line = TRUE, sort = "asc")


# \donttest{
gglikert_stacked(df_group, q1:q6, y = "group", add_median_line = TRUE) +
  facet_grid(rows = vars(.question))

# }