guideR (version 0.8.1)

plot_multiple_answers: Plot a multiple answers question

Description

Considering a multiple answers question coded as several binary variables (one per answer), plot the proportion of positive answers. If combine_answers = FALSE, plot the proportion of positive answers of each item, separately. If combine_answers = FALSE, combine the different answers (see combine_answers()) and plot the proportion of each combination (ggupset package required when flip = FALSE). See proportion() for more details on the way proportions and confidence intervals are computed. By default, return a bar plot, but other geometries could be used (see examples). If defined, use variable labels (see examples).

Usage

plot_multiple_answers(
  data,
  answers = dplyr::everything(),
  value = NULL,
  by = NULL,
  combine_answers = FALSE,
  combine_sep = " | ",
  missing_label = " missing",
  none_label = "none",
  drop_na = FALSE,
  drop_na_by = FALSE,
  sort = c("none", "ascending", "descending", "degrees"),
  geom = "bar",
  ...,
  show_ci = TRUE,
  conf_level = 0.95,
  ci_color = "black",
  show_labels = TRUE,
  labels_labeller = scales::label_percent(1),
  labels_size = 3.5,
  labels_color = "black",
  flip = FALSE,
  return_data = FALSE
)
plot_multiple_answers_dodge(
  data,
  answers = dplyr::everything(),
  value = NULL,
  by,
  combine_answers = FALSE,
  combine_sep = " | ",
  missing_label = " missing",
  none_label = "none",
  drop_na = FALSE,
  drop_na_by = FALSE,
  sort = c("none", "ascending", "descending", "degrees"),
  geom = c("bar", "point"),
  width = 0.75,
  ...,
  show_ci = TRUE,
  conf_level = 0.95,
  ci_color = "black",
  show_labels = TRUE,
  labels_labeller = scales::label_percent(1),
  labels_size = 3.5,
  labels_color = "black",
  flip = FALSE
)

Arguments

data

A data frame, data frame extension (e.g. a tibble), or a survey design object.

answers

<tidy-select> List of variables identifying the different answers of the question.

value

Value indicating a positive answer. By default, will use the maximum observed value and will display a message.

by

<tidy-select> Optional list of variables to compare (using facets).

combine_answers

Should answers be combined? (see examples)

combine_sep

Character string to separate combined answers.

missing_label

When combining answers and drop_na = FALSE, label for missing values.

none_label

When combining answers and flip = TRUE, label when no item is selected.

drop_na

Should any observation with a least one NA value be dropped?

drop_na_by

If TRUE, will remove any NA values observed in the by variables

sort

Should answers be sorted according to their proportion? They could also be sorted by degrees (number of elements) when combining answers.

geom

Geometry to use for plotting proportions ("bar" by default).

...

Additional arguments passed to the geom defined by geom.

show_ci

Display confidence intervals?

conf_level

Confidence level for the confidence intervals.

ci_color

Color of the error bars representing confidence intervals.

show_labels

Display proportion labels?

labels_labeller

Labeller function for proportion labels.

labels_size

Size of proportion labels.

labels_color

Color of proportion labels.

flip

Flip x and y axis?

return_data

Return computed data instead of the plot?

width

Dodging width.

Examples

d <-
  dplyr::tibble(
    q1a = sample(c("y", "n"), size = 200, replace = TRUE),
    q1b = sample(c("y", "n", "n", NA), size = 200, replace = TRUE),
    q1c = sample(c("y", "y", "n"), size = 200, replace = TRUE),
    q1d = sample("n", size = 200, replace = TRUE)
  )

d |> plot_multiple_answers(q1a:q1c)

d |>
  labelled::set_variable_labels(
    q1a = "apple",
    q1b = "banana",
    q1c = "chocolate",
    q1d = "Dijon mustard"
  ) |>
  plot_multiple_answers(
    value = "y",
    drop_na = TRUE,
    sort = "desc",
    fill = "lightblue",
    flip = TRUE
  )
if (FALSE) { # rlang::is_installed("ggupset")
# \donttest{
d |>
  plot_multiple_answers(
    combine_answers = TRUE,
    value = "y",
    fill = "#DDCC77",
    drop_na = TRUE
  )

d |>
  plot_multiple_answers(
    combine_answers = TRUE,
    value = "y",
    flip = TRUE,
    mapping = ggplot2::aes(fill = prop),
    show.legend = FALSE
  ) +
  ggplot2::scale_fill_distiller(palette = "Spectral")

d$group <- sample(c("group A", "group B"), size = 200, replace = TRUE)
d |>
  plot_multiple_answers(
    answers = q1a:q1d,
    by = group,
    combine_answers = TRUE,
    sort = "degrees",
    value = "y",
    fill = "grey80"
  )

d |>
  plot_multiple_answers_dodge(q1a:q1d, by = group)
d |>
  plot_multiple_answers_dodge(q1a:q1d, by = group, flip = TRUE)
d |>
  plot_multiple_answers_dodge(q1a:q1d, by = group, combine_answers = TRUE)
# }
}
if (FALSE) { # rlang::is_installed(c("ggupset", "ggstats"))
}