Build a weighting-policy review between Rasch-family and bounded GPCM fits
Source:R/api-advanced.R
build_weighting_review.RdBuild a weighting-policy review between Rasch-family and bounded GPCM fits
Usage
build_weighting_review(
rasch_fit,
gpcm_fit,
theta_range = c(-6, 6),
theta_points = 101L,
top_n = 10L
)Arguments
- rasch_fit
Output from
fit_mfrm()usingmodel = "RSM"or"PCM".- gpcm_fit
Output from
fit_mfrm()using boundedmodel = "GPCM".- theta_range
Numeric vector of length 2 passed to
compute_information()for the information-redistribution comparison.- theta_points
Integer number of theta grid points passed to
compute_information().- top_n
Maximum number of rows to keep in compact summary outputs.
Details
build_weighting_review() is an operational model-choice review helper. It
is designed for the common question:
what changes when a Rasch-family equal-weighting model is replaced with a bounded
GPCMthat allows discrimination-based reweighting?
The helper does not estimate a new model. Instead, it synthesizes four package-native evidence sources:
compare_mfrm()for same-data model comparisonthe non-person facet measures from each fit
the bounded
GPCMslope tablecompute_information()for design-weighted information redistribution
The result is intended for substantive review, not for automatic model
selection. In particular, a better-fitting GPCM should not by itself be
interpreted as a reason to discard an equal-weighting Rasch-family route.
Recommended input route
Fit an equal-weighting reference model with
model = "RSM"or"PCM".Fit a bounded
GPCMon the same prepared response data.Run
build_weighting_review(rasch_fit, gpcm_fit).Read
summary(review)before deciding whether the discrimination-based reweighting is substantively acceptable.
What the returned tables mean
model_comparison: same-data model-comparison bundle fromcompare_mfrm().facet_shift: how non-person facet estimates move under boundedGPCM.slope_profile: whichslope_facetlevels are upweighted or downweighted.information_redistribution: within-facet information-share changes between the Rasch-family fit and boundedGPCM.top_reweighted_levels: compact triage table for the strongest slope-facet-level redistribution signals.
GPCM boundary
This helper is available only for the current bounded GPCM branch. It
requires the package's existing slope_facet == step_facet contract and
should be read as an operational weighting-policy review, not as a formal
validity adjudication.
Examples
# \donttest{
toy <- load_mfrmr_data("example_core")
rasch_fit <- fit_mfrm(
toy,
"Person",
c("Rater", "Criterion"),
"Score",
method = "MML",
model = "RSM",
quad_points = 9
)
gpcm_fit <- fit_mfrm(
toy,
"Person",
c("Rater", "Criterion"),
"Score",
method = "MML",
model = "GPCM",
step_facet = "Criterion",
slope_facet = "Criterion",
quad_points = 9
)
review <- build_weighting_review(rasch_fit, gpcm_fit, theta_points = 41)
summary(review)
#> mfrm Weighting Review Summary
#>
#> Overview
#> ReferenceModel ComparisonModel ReferenceMethod ComparisonMethod SlopeFacet
#> RSM GPCM MML MML Criterion
#> ReviewStatus ComparisonMode MaxAbsLogSlope
#> reweighting_review_required same_basis_fit_comparison 0.138
#> MaxAbsInfoShareDelta
#> 0.024
#>
#> Status
#> Item
#> Overall status
#> Weighting principle
#> Comparison basis
#> Value
#> reweighting_review_required
#> Rasch-family equal weighting vs bounded GPCM discrimination-based reweighting
#> same_basis_fit_comparison
#>
#> Key Warnings
#> - Largest bounded GPCM slope deviation is at Criterion = Organization
#> (Estimate = 1.148).
#> - Largest within-facet information-share shift is -0.024 for Criterion =
#> Organization.
#> - Largest facet-measure shift is -0.032 for Criterion = Content.
#>
#> Next Actions
#> - Read summary(model_comparison) before interpreting any fit advantage as a
#> scoring recommendation.
#> - Use slope_profile and top_reweighted_levels to inspect whether Criterion
#> levels are being upweighted or downweighted in substantively acceptable
#> ways.
#> - Use plot_information(compute_information(rasch_fit), type = "iif", facet =
#> "Criterion", draw = FALSE) and the bounded GPCM analogue to inspect
#> precision redistribution visually.
#> - If equal contributions of items and raters are part of the score
#> interpretation, retain the Rasch-family fit as the operational reference
#> even when bounded GPCM fits better.
#>
#> Top Measure Shifts
#> Facet Level ReferenceEstimate ReferenceRank ComparisonEstimate
#> Criterion Content -0.401 1 -0.433
#> Criterion Language 0.094 3 0.122
#> Criterion Accuracy 0.240 4 0.258
#> Criterion Organization 0.067 2 0.053
#> Rater R03 0.184 3 0.177
#> Rater R04 0.321 4 0.329
#> Rater R01 -0.189 2 -0.188
#> Rater R02 -0.317 1 -0.318
#> ComparisonRank DeltaEstimate AbsDeltaEstimate RankShift Direction
#> 1 -0.032 0.032 0 Lower in bounded GPCM
#> 3 0.028 0.028 0 Higher in bounded GPCM
#> 4 0.018 0.018 0 Higher in bounded GPCM
#> 2 -0.014 0.014 0 Lower in bounded GPCM
#> 3 -0.008 0.008 0 Lower in bounded GPCM
#> 4 0.007 0.007 0 Higher in bounded GPCM
#> 2 0.001 0.001 0 Higher in bounded GPCM
#> 1 -0.001 0.001 0 Lower in bounded GPCM
#>
#> Top Reweighted Levels
#> Facet Level ReferenceIntegratedInfo ReferenceExposure
#> Criterion Organization 1909.750 192
#> Criterion Accuracy 1909.445 192
#> Criterion Content 1909.047 192
#> Criterion Language 1909.722 192
#> ReferenceInfoShare ReferenceExposureShare ComparisonIntegratedInfo
#> 0.25 0.25 2196.386
#> 0.25 0.25 1730.686
#> 0.25 0.25 1757.373
#> 0.25 0.25 1983.700
#> ComparisonExposure ComparisonInfoShare ComparisonExposureShare InfoShareDelta
#> 192 0.226 0.25 -0.024
#> 192 0.226 0.25 -0.024
#> 192 0.226 0.25 -0.024
#> 192 0.226 0.25 -0.024
#> ExposureShareDelta IntegratedInfoRatio AbsInfoShareDelta AbsLogInfoRatio
#> 0 1.150 0.024 0.140
#> 0 0.906 0.024 0.098
#> 0 0.921 0.024 0.083
#> 0 1.039 0.024 0.038
#> SlopeEstimate SlopeLogEstimate SlopeDirection SlopeExposure SlopeExposureShare
#> 1.148 0.138 Upweighted 192 0.25
#> 0.910 -0.094 Downweighted 192 0.25
#> 0.924 -0.079 Downweighted 192 0.25
#> 1.036 0.036 Near unit 192 0.25
#>
#> Support Status
#> Scope Status
#> RSM / PCM reference supported
#> bounded GPCM comparison supported_with_caveat
#> Note
#> Supported as the equal-weighting reference side of the review.
#> Supported with caveat as a slope-aware comparison model. Use it to inspect discrimination-based reweighting, not as an automatic replacement for the Rasch-family route.
#>
#> Notes
#> - Observation weights and discrimination-based reweighting are separate
#> concepts in this package.
#> - The review is intended to make reweighting visible; it does not decide by
#> itself whether bounded GPCM should replace the Rasch-family operational
#> model.
#> - Information-share changes are computed within each facet because the same
#> total information is partitioned separately by facet.
review$top_reweighted_levels
#> # A tibble: 4 × 20
#> Facet Level ReferenceIntegratedI…¹ ReferenceExposure ReferenceInfoShare
#> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 Criterion Organiz… 1910. 192 0.250
#> 2 Criterion Accuracy 1909. 192 0.250
#> 3 Criterion Content 1909. 192 0.250
#> 4 Criterion Language 1910. 192 0.250
#> # ℹ abbreviated name: ¹ReferenceIntegratedInfo
#> # ℹ 15 more variables: ReferenceExposureShare <dbl>,
#> # ComparisonIntegratedInfo <dbl>, ComparisonExposure <dbl>,
#> # ComparisonInfoShare <dbl>, ComparisonExposureShare <dbl>,
#> # InfoShareDelta <dbl>, ExposureShareDelta <dbl>, IntegratedInfoRatio <dbl>,
#> # AbsInfoShareDelta <dbl>, AbsLogInfoRatio <dbl>, SlopeEstimate <dbl>,
#> # SlopeLogEstimate <dbl>, SlopeDirection <chr>, SlopeExposure <dbl>, …
# }