Extract model-estimated facet interaction effects

interaction_effect_table() returns the fixed-effect interaction block estimated by fit_mfrm() when facet_interactions is supplied. These are model-estimated deviations from the additive main-effects MFRM, not the residual screening statistics returned by estimate_bias().

Usage

interaction_effect_table(fit)

Arguments

fit

An mfrm_fit object returned by fit_mfrm().

Value

A tibble with one row per interaction cell. Returns an empty tibble when the fit has no model-estimated facet interactions.

Details

The current release supports two-way interactions between non-person facets, for example facet_interactions = "Rater:Criterion". Each interaction matrix is identified by zero marginal sums across both participating facets, so the interaction estimates are separable from the two main effects. Positive values indicate higher-than-expected scores for the facet-level combination under the additive model; negative values indicate lower-than-expected scores.

Use this table for confirmatory model review after specifying the facet pair of substantive interest. For exploratory screening without adding parameters to the fitted model, use estimate_bias() or estimate_all_bias().

See also

fit_mfrm(), estimate_bias(), compare_mfrm()

Examples

toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(
  toy, person = "Person", facets = c("Rater", "Criterion"),
  score = "Score", method = "JML", model = "RSM", maxit = 30
)
interaction_effect_table(fit)
#> # A tibble: 0 × 0