Summarize model agreement across analysis levels — model_agreement

Builds a slide-ready sensitivity table by running model_agreement() across several substantively useful unit definitions (for example book-level, chapter-level, and party-specific agreement). Lower-level rows are aggregated with an NA-safe mean before each agreement calculation, so skipped chapters do not turn an entire book mean into NA.

Usage

model_agreement_sensitivity(
  data,
  outcome = "mean_outcome",
  model_col = "model",
  analyses = NULL,
  metrics = c("icc", "kendall_w"),
  format = c("wide", "long"),
  digits = 2,
  drop_missing = TRUE
)

Arguments

data: A data frame with one row per model-by-unit combination.
outcome: Character string naming the score column (default "mean_outcome").
model_col: Character string naming the model column (default "model").
analyses: Optional named list defining analyses to run. Each element should be a list with unit_by and, optionally, group_by. If NULL, a default set is inferred from available book, chapter, and party/group columns.
metrics: Character vector of metrics to compute. One or both of "icc" and "kendall_w" (default both).
format: Character. "wide" returns one row per analysis/subgroup with ICC and Kendall's W side by side; "long" returns the stacked model_agreement() results with analysis labels.
digits: Integer. Number of decimal places used in the formatted wide table.
drop_missing: Logical. Whether to drop rows with missing model, unit, or grouping identifiers before computing each analysis (default TRUE).

Value

A tibble. With format = "wide", columns include Analysis level, Subgroup, N models, N units, ICC, and Kendall's W.

Examples

if (FALSE) { # \dontrun{
model_agreement_sensitivity(
  agg,
  outcome = "mean_delta_gap",
  model_col = "model"
)
} # }