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Likert Summary

Source: R/tbl_likert.R
tbl_likert.Rd

[Experimental]
Create a table of ordered categorical variables in a wide format.

Usage

tbl_likert(
  data,
  statistic = ~"{n} ({p}%)",
  label = NULL,
  digits = NULL,
  include = everything(),
  sort = c("ascending", "descending")
)

Arguments

data

(data.frame)
A data frame.

statistic

(formula-list-selector)
Used to specify the summary statistics for each variable. The default is everything() ~ "{n} ({p}%)".

label

(formula-list-selector)
Used to override default labels in summary table, e.g. list(age = "Age, years"). The default for each variable is the column label attribute, attr(., 'label'). If no label has been set, the column name is used.

digits

(formula-list-selector)
Specifies how summary statistics are rounded. Values may be either integer(s) or function(s). If not specified, default formatting is assigned via assign_summary_digits().

include

(tidy-select)
Variables to include in the summary table. Default is everything().

sort

(string)
indicates whether levels of variables should be placed in ascending order (the default) or descending.

Value

a 'tbl_likert' gtsummary table

Examples

levels <- c("Strongly Disagree", "Disagree", "Agree", "Strongly Agree")
df_likert <- data.frame(
  recommend_friend = sample(levels, size = 20, replace = TRUE) |> factor(levels = levels),
  regret_purchase = sample(levels, size = 20, replace = TRUE) |> factor(levels = levels)
)

# Example 1 ----------------------------------
tbl_likert_ex1 <-
  df_likert |>
  tbl_likert(include = c(recommend_friend, regret_purchase)) |>
  add_n()
tbl_likert_ex1



  
Characteristic
      N
      Strongly Disagree
      Disagree
      Agree
      Strongly Agree
    
recommend_friend
20
9 (45%)
4 (20%)
4 (20%)
3 (15%)
regret_purchase
20
4 (20%)
2 (10%)
7 (35%)
7 (35%)

# Example 2 ----------------------------------
# Add continuous summary of the likert scores
list(
  tbl_likert_ex1,
  tbl_wide_summary(
    df_likert |> dplyr::mutate(dplyr::across(everything(), as.numeric)),
    statistic = c("{mean}", "{sd}"),
    type = ~"continuous",
    include = c(recommend_friend, regret_purchase)
  )
) |>
  tbl_merge(tab_spanner = FALSE)



  
Characteristic
      N
      Strongly Disagree
      Disagree
      Agree
      Strongly Agree
      Mean
      SD
    
recommend_friend
20
9 (45%)
4 (20%)
4 (20%)
3 (15%)
2.05
1.15
regret_purchase
20
4 (20%)
2 (10%)
7 (35%)
7 (35%)
2.85
1.14