Data Cleaning and Preparation in R

Handling Missing Data in Cleaning Workflows

Code Example 4

30-45 minutes Applied Step 10 of 11

Code

Code Example 4

10 / 11

Code

Code Example 4

site_missingness <- enrollment_data |>
  group_by(site) |>
  summarise(
    n_records = n(),
    missing_consent_dates = sum(is.na(consent_date)),
    missing_primary_outcome = sum(is.na(primary_outcome)),
    percent_missing_primary_outcome = 100 * missing_primary_outcome / n_records,
    .groups = "drop"
  )

site_missingness