clinpubr (version 1.1.1)

exclusion_count: Count the number of excluded samples at each step

Description

This function sequentially applies exclusion criteria to a data frame and counts the number of samples removed at each step.

Usage

exclusion_count(.df, ..., .criteria_names = NULL, .na_exclude = TRUE)

Value

A data frame with two columns: 'Criteria' and 'N', showing the number of samples at the start, the number excluded at each step, and the final number remaining.

Arguments

.df

A data frame.

...

Exclusion criteria. Logical expressions that define which rows to exclude.

.criteria_names

An optional character vector of names for the criteria. If NULL, the expressions themselves are used as names.

.na_exclude

A logical value. If TRUE, rows where the criterion evaluates to NA will be excluded, and a warning will be issued. Defaults to FALSE, where NA values are not excluded.

Examples

cohort <- data.frame(
  age = c(17, 25, 30, NA, 50, 60),
  sex = c("M", "F", "F", "M", "F", "M"),
  value = c(1, NA, 3, 4, 5, NA),
  dementia = c(TRUE, FALSE, FALSE, FALSE, TRUE, FALSE)
)
exclusion_count(
  cohort,
  age < 18,
  is.na(value),
  dementia == TRUE,
  .criteria_names = c(
    "Age < 18 years",
    "Missing value",
    "History of dementia"
  )
)