Descriptive tables with {gtsummary}

What is {gtsummary}?

• Create tables that are publication-ready
• Highly customizable
• Descriptive tables, regression tables, etc.

gtsummary::tbl_summary()

library(gtsummary)

tbl_summary(
  nlsy,
  by = sex_cat,
  include = c(sex_cat, race_eth_cat, region_cat,
              eyesight_cat, glasses, age_bir))

You can also refer to variables using helper functions

library(gtsummary)

tbl_summary(
  nlsy,
  by = sex_cat,
  include = c(ends_with("cat"), glasses, age_bir))

Additional arguments

We saw include =, by =, label =, missing_text = in the example

statistic =:

• The default is list(all_continuous() ~ "{median} ({p25}, {p75})", all_categorical() ~ "{n} ({p}%)")
• For categorical variables, you can use {n} (frequency), {N} (denominator), {p} formatted percentage
• For continuous variables, you can use {median}, {mean}, {sd}, {var}, {min}, {max}, {sum}, ⁠{p##} (any percentile), or any function {foo}
• You can refer to individual variables with their names: list(age ~ "min = {min}; max = {max}")

Additional arguments

digits =:

• It will do its best to guess the appropriate number of digits
• Otherwise, you can pass a function:
  • digits = everything() ~ style_sigfig
• Or a value for each statistic shown
  • statistic = list(age ~ "min = {min}; max = {max}", year_of_birth = "{median} ({p25}, {p75})") :
  • digits = list(age ~ c(1, 1) year_of_birth ~ c(0, 0, 0))

Additional arguments

type =:

• One of “continuous”, “continuous2”, “categorical”, “dichotomous”
  • If a variable only has 0/1, TRUE/FALSE, or yes/no values, it will be treated as dichotomous
    • You can override this with type = list(``varname``~ "categorical")
    • Dichotomous variables only show one row (i.e., the percentage of 1’s) unless you change to categorical
      • You can change which level to show with value = list(varname ~ "level to show")
  • “continuous2” variables can have multiple rows of statistics

missing =:

• Show NA values in the table (“no”, “ifany”, “always”)

Additional functions

• add_overall(): In a stratified table, add a column for all strata combined
• bold_labels(): Bold the variable names (also bold_levels())
• add_p(): Add a p-value (required by some journals 🤷‍♀️)
• modify_footnote(update = everything() ~ NA): Remove the footnotes (can also add footnotes!)
• modify_header(): Change the header column

tbl_summary()

• Incredibly customizeable

  • So many options can be overwhelming
  • The FAQ/gallery is an incredible resource

• To save, I often just view in the web browser and copy and paste into a Word document

  • Can also be used within quarto/R Markdown

Exercises

1. Download the script with some examples and save in your in-class project directory.

2. Install {gtsummary} and run the examples.

3-7. You’re on your own! Work with your neighbors, and we’ll come back together to go over these.

Extra time? Start a table using the data you downloaded for your final project! Make sure you switch to that R project!