Describe an rbmi Imputation Object

Extracts structured metadata from an rbmi imputation object, including method, number of imputations (M), reference arm mappings, subject count, and a missingness breakdown by visit and treatment arm. Returns an S3 object with an informative print() method.

Usage

describe_imputation(impute_obj)

Arguments

impute_obj

An imputation object returned by rbmi::impute().

Value

An S3 object of class c("describe_imputation", "list") containing:

method

Human-readable method name (e.g., "Bayesian (MCMC via Stan)")

method_class

Raw class name: "bayes", "approxbayes", or "condmean"

n_imputations

Number of imputations (M)

references

Named character vector of reference arm mappings, or NULL

n_subjects

Total number of unique subjects

visits

Character vector of visit names

missingness

A data.frame with columns: visit, group, n_total, n_miss, pct_miss

Details

The missingness table is built by cross-tabulating impute_obj$data$is_missing by visit and treatment group. Each row shows the total number of subjects in that group, how many had missing data at that visit, and the percentage missing.

See also

• rbmi::impute() to create imputation objects

• describe_draws() for inspecting draws objects

Examples

if (FALSE) { # \dontrun{
library(rbmi)
library(dplyr)
data("ADEFF", package = "rbmiUtils")

ADEFF <- ADEFF |>
  mutate(
    TRT = factor(TRT01P, levels = c("Placebo", "Drug A")),
    USUBJID = factor(USUBJID),
    AVISIT = factor(AVISIT, levels = c("Week 24", "Week 48"))
  )

vars <- set_vars(
  subjid = "USUBJID", visit = "AVISIT", group = "TRT",
  outcome = "CHG", covariates = c("BASE", "STRATA", "REGION")
)
dat <- ADEFF |> select(USUBJID, STRATA, REGION, TRT, BASE, CHG, AVISIT)
draws_obj <- draws(
  data = dat, vars = vars,
  method = method_bayes(n_samples = 100)
)
impute_obj <- impute(
  draws_obj,
  references = c("Placebo" = "Placebo", "Drug A" = "Placebo")
)

# Inspect the imputation
desc <- describe_imputation(impute_obj)
print(desc)

# Programmatic access
desc$n_imputations
desc$missingness
desc$references
} # }