| summary.mfrm_bias | R Documentation |
mfrm_bias object in a user-friendly formatSummarize an mfrm_bias object in a user-friendly format
## S3 method for class 'mfrm_bias'
summary(object, digits = 3, top_n = 10, p_cut = 0.05, ...)
object |
Output from |
digits |
Number of digits for printed numeric values. |
top_n |
Number of strongest bias rows to keep. |
p_cut |
Significance cutoff used for counting flagged rows. |
... |
Reserved for generic compatibility. |
This method returns a compact interaction-bias summary:
interaction facets/order and analyzed cell counts
effect-size profile (|bias| mean/max, significant cell count)
fixed-effect chi-square block
iteration-end convergence indicators
top rows ranked by absolute t
An object of class summary.mfrm_bias with:
overview: interaction facets/order, cell counts, and effect-size profile
chi_sq: fixed-effect chi-square block
final_iteration: end-of-iteration status row
top_rows: highest-|t| interaction rows
notes: short interpretation notes
overview: interaction order, analyzed cells, and effect-size profile.
chi_sq: fixed-effect test block.
final_iteration: end-of-loop status from the bias routine.
top_rows: strongest bias contrasts by |t|.
Estimate interactions with estimate_bias().
Check summary(bias) for screen-positive and unstable cells.
Use bias_interaction_report() or plot_bias_interaction() for details.
estimate_bias(), bias_interaction_report()
toy <- load_mfrmr_data("example_bias")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
diag <- diagnose_mfrm(fit, residual_pca = "none")
bias <- estimate_bias(fit, diag, facet_a = "Rater", facet_b = "Criterion", max_iter = 2)
summary(bias)
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