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Prediction Contrasts, Rankings, and Groups

Prediction grids can be summarised by observed design variables without expanding the approved model-family scope.

grid <- create_prediction_grid(
  fit,
  at = list(condition = c("control", "treatment"))
)

pred <- predict_model(
  fit,
  newdata = grid,
  type = "expected",
  include_group_effects = FALSE
)

prediction_pairwise_contrasts(pred)
prediction_interval_width(pred)
prediction_rank_probabilities(pred)

The ranking function is deliberately descriptive. A probability of rank one is not converted into an automatic selection.

When the prediction data contain multiple rows per substantive group:

grouped <- group_prediction_summary(pred, by = "condition")
grouped
plot_group_predictions(grouped, "condition")

This makes aggregation explicit and reproducible rather than hiding it inside plotting code.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.