proportion_summary {gtsummary}

Summarize a proportion

Description

This helper, to be used with tbl_custom_summary(), creates a function computing a proportion and its confidence interval.

Usage

proportion_summary(
  variable,
  value,
  weights = NULL,
  na.rm = TRUE,
  conf.level = 0.95,
  method = c("wilson", "wilson.no.correct", "wald", "wald.no.correct", "exact",
    "agresti.coull", "jeffreys")
)

Arguments

variable

(string)
String indicating the name of the variable from which the proportion will be computed.

value

(scalar)
Value (or list of values) of variable to be taken into account in the numerator.

weights

(string)
Optional string indicating the name of a frequency weighting variable. If NULL, all observations will be assumed to have a weight equal to 1.

na.rm

(scalar logical)
Should missing values be removed before computing the proportion? (default is TRUE)

conf.level

(scalar numeric)
Confidence level for the returned confidence interval. Must be strictly greater than 0 and less than 1. Default to 0.95, which corresponds to a 95 percent confidence interval.

method

(string)
Confidence interval method. Must be one of c("wilson", "wilson.no.correct", "wald", "wald.no.correct", "exact", "agresti.coull", "jeffreys"). See add_ci() for details.

Details

Computed statistics:

• {n} numerator, number of observations equal to values

• {N} denominator, number of observations

• {prop} proportion, i.e. n/N

• {conf.low} lower confidence interval

• {conf.high} upper confidence interval

Methods c("wilson", "wilson.no.correct") are calculated with stats::prop.test() (with correct = c(TRUE, FALSE)). The default method, "wilson", includes the Yates continuity correction. Methods c("exact", "asymptotic") are calculated with Hmisc::binconf() and the corresponding method.

Author(s)

Joseph Larmarange

Examples

# Example 1 ----------------------------------
Titanic |>
  as.data.frame() |>
  tbl_custom_summary(
    include = c("Age", "Class"),
    by = "Sex",
    stat_fns = ~ proportion_summary("Survived", "Yes", weights = "Freq"),
    statistic = ~ "{prop}% ({n}/{N}) [{conf.low}-{conf.high}]",
    digits = ~ list(
      prop = label_style_percent(digits = 1),
      n = 0,
      N = 0,
      conf.low = label_style_percent(),
      conf.high = label_style_percent()
    ),
    overall_row = TRUE,
    overall_row_last = TRUE
  ) |>
  bold_labels() |>
  modify_footnote(all_stat_cols() ~ "Proportion (%) of survivors (n/N) [95% CI]")