View source: R/api-estimation.R
| make_anchor_table | R Documentation |
Build an anchor table from fitted estimates
make_anchor_table(fit, facets = NULL, include_person = FALSE, digits = 6)
fit |
Output from |
facets |
Optional subset of facets to include. |
include_person |
Include person estimates as anchors. |
digits |
Rounding digits for anchor values. |
This function exports estimated facet parameters as an anchor table for use in subsequent calibrations. This is the standard approach for linking across administrations: a reference run establishes the measurement scale, and anchored re-analyses place new data on that same scale.
Anchor values should be exported from a well-fitting reference run
with adequate sample size. If the reference model has convergence
issues or large misfit, the exported anchors may propagate
instability. Re-run audit_mfrm_anchors() on the receiving data
to verify compatibility before estimation.
The digits parameter controls rounding precision. Use at least 4
digits for research applications; excessive rounding (e.g., 1 digit)
can introduce avoidable calibration error.
A data.frame with Facet, Level, and Anchor.
Facet: facet name to be anchored in later runs.
Level: specific element/level name inside that facet.
Anchor: fixed logit value (rounded by digits).
Fit a reference run with fit_mfrm().
Export anchors with make_anchor_table(fit).
Pass selected rows back into fit_mfrm(..., anchors = ...).
fit_mfrm(), audit_mfrm_anchors()
toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
anchors_tbl <- make_anchor_table(fit)
head(anchors_tbl)
summary(anchors_tbl$Anchor)
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