| build_model_choice_review | R Documentation |
Build a model-choice review across RSM, PCM, and bounded GPCM fits
build_model_choice_review(
...,
labels = NULL,
run_weighting_review = NULL,
theta_range = c(-6, 6),
theta_points = 61L,
top_n = 10L,
warn_constraints = TRUE
)
... |
Two or more fitted |
labels |
Optional labels for the supplied fits. If omitted, names from
|
run_weighting_review |
Logical. If |
theta_range, theta_points, top_n |
Passed to |
warn_constraints |
Passed to |
build_model_choice_review() is a user-facing synthesis helper. It does not
estimate new models. It bundles:
compare_mfrm() for AIC/BIC/log-likelihood comparison;
model-role guidance for RSM, PCM, and bounded GPCM;
downstream-route availability for APA output, score-side export, linking, recovery, fair averages, bias screening, and summary-appendix handoff;
report wording templates that avoid treating better bounded-GPCM fit as
an automatic operational-scoring decision;
gpcm_capability_matrix() when bounded GPCM is present;
optionally, build_weighting_review() for the first Rasch-family reference
versus bounded-GPCM pair.
The word "bounded" is intentional: the package implements a bounded GPCM
route, not every possible generalized partial-credit many-facet extension.
The current route uses positive slopes, requires slope_facet == step_facet,
identifies slopes on the log scale with geometric mean 1, and keeps several
downstream score-side/reporting helpers outside the validated boundary.
An object of class mfrm_model_choice_review.
compare_mfrm(), build_weighting_review(),
gpcm_capability_matrix(), compute_information()
toy <- load_mfrmr_data("example_core")
fit_rsm <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
method = "MML", model = "RSM", quad_points = 7)
fit_pcm <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
method = "MML", model = "PCM", step_facet = "Criterion",
quad_points = 7)
review <- build_model_choice_review(RSM = fit_rsm, PCM = fit_pcm)
summary(review)
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