Audit Missingness Structure Before Model Fitting — audit_missingness

Summarises missing values in declared analysis columns and, where possible, by participant, item, and condition. This is a reporting audit; no rows are dropped or imputed.

Usage

audit_missingness_structure(
  x,
  contract = NULL,
  review_fraction = 0.05,
  fail_fraction = 0.2
)

Arguments

x: A data frame, prepared object, model specification, or fit.
contract: Required when x is a raw data frame.
review_fraction: Column-level missing fraction above which a component is marked for review.
fail_fraction: Column-level missing fraction above which a component is marked fail. A fail does not automatically exclude data.

Value

A gp3bayes_missingness_audit.

Examples

data <- data.frame(
  participant_id = rep(c("p1", "p2"), each = 4),
  trial_id = rep(1:4, 2),
  condition = rep(c("control", "treatment"), 4),
  selected = c(0, 1, NA, 1, 1, 0, 1, 0)
)
contract <- create_model_contract(
  "binary", "selected", "participant_id",
  trial_col = "trial_id", condition_col = "condition"
)
audit_missingness_structure(data, contract)
#> <gp3bayes_missingness_audit>
#>   Status: review
#>   Rows: 8
#>   Missing cells: 1