read_facets_fit_table: Read a FACETS fit table for fit review

In mfrmr: Estimation and Diagnostics for Many-Facet Measurement Models

Read a FACETS fit table for fit review

Description

Read a FACETS fit table for fit review

Usage

read_facets_fit_table(
  file,
  facet = NULL,
  facet_map = NULL,
  format = c("auto", "delimited", "scorefile"),
  facet_col = NULL,
  level_col = NULL,
  delimiter = NULL,
  encoding = "UTF-8"
)

import_facets_fit_table(
  file,
  facet = NULL,
  facet_map = NULL,
  format = c("auto", "delimited", "scorefile"),
  facet_col = NULL,
  level_col = NULL,
  delimiter = NULL,
  encoding = "UTF-8"
)

Arguments

file	Path to a FACETS-derived fit table. A character vector of files is accepted. A directory containing score.N.txt files is also accepted.
facet	Optional facet name to assign when the file does not contain a facet column. Use this for one-facet CSV exports.
facet_map	Optional character vector mapping FACETS score-file numbers to facet names, for example c("1" = "Person", "2" = "Rater"). If unnamed, positions are used as score-file numbers.
format	File format. "auto" detects FACETS score.N.txt files from their name/header; "delimited" reads a CSV/TSV/semicolon table; and "scorefile" reads a FACETS score-file table.
facet_col, level_col	Optional explicit column names for delimited tables when automatic detection is not sufficient. For score files, level_col can override the column immediately before F-Number.
delimiter	Optional delimiter for delimited tables. If omitted, comma, tab, and semicolon are detected from the header line.
encoding	File encoding passed to readLines().

Details

This helper does not run FACETS. It reads FACETS output that already exists on disk and normalizes it to columns that facets_fit_review() can consume: Facet, Level, Estimate, SE, N, Infit, Outfit, InfitZSTD, OutfitZSTD, DF_Infit, and DF_Outfit.

Two common workflows are supported:

• a FACETS score file such as score.2.txt, where the facet name is supplied by facet_map or inferred as Facet2. Both comma-delimited score files with field names and fixed-field score files using the FACETS manual column positions are supported;

• a CSV/TSV table already exported from FACETS or a harmonization script, with FACETS-style column names such as ⁠Infit MnSq⁠, ⁠Outfit ZStd⁠, and T.Count.

After import, pass the table to facets_fit_review(). Inspect review$external_table_quality first when the FACETS export is partial, duplicated, or missing MnSq/df columns. Then inspect review$external_comparison for supplied FACETS-vs-mfrmr differences and review$df_sensitivity / review$df_sensitive for engine-vs-FACETS-style df/ZSTD convention sensitivity. Use plot(review, type = "df_sensitivity") for a quick visual check of the largest ZSTD shifts caused by df convention.

Value

A tibble with standardized fit-table columns suitable for facets_fit_review(fit, facets_fit = read_facets_fit_table(...)).

See Also

facets_fit_review(), diagnose_mfrm()

Examples

path <- tempfile(fileext = ".csv")
write.csv(
  data.frame(
    Facet = "Rater", Level = "R1", Infit = 1.02, Outfit = 0.98,
    InfitZSTD = 0.3, OutfitZSTD = -0.2, DF_Infit = 12, DF_Outfit = 13
  ),
  path,
  row.names = FALSE
)
read_facets_fit_table(path)

mfrmr documentation built on June 13, 2026, 1:07 a.m.