ej2021_data: Simulated MFRM datasets based on Eckes and Jin (2021)

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

Simulated MFRM datasets based on Eckes and Jin (2021)

Description

Synthetic many-facet rating datasets in long format. All datasets include one row per observed rating.

Format

A data.frame with 5 columns:

Study

Study label ("Study1" or "Study2").

Person

Person/respondent identifier.

Rater

Rater identifier.

Criterion

Criterion facet label.

Score

Observed category score.

Details

Available data objects:

• mfrmr_example_core

• mfrmr_example_bias

• ej2021_study1

• ej2021_study2

• ej2021_combined

• ej2021_study1_itercal

• ej2021_study2_itercal

• ej2021_combined_itercal

Naming convention:

• study1 / study2: separate simulation studies

• combined: row-bind of study1 and study2

• ⁠_itercal⁠: iterative-calibration variant

Use load_mfrmr_data() for programmatic selection by key.

Data dimensions

Dataset	Rows	Persons	Raters	Criteria
study1	1842	307	18	3
study2	3287	206	12	9
combined	5129	307	18	12
study1_itercal	1842	307	18	3
study2_itercal	3341	206	12	9
combined_itercal	5183	307	18	12

Score range: 1–4 (four-category rating scale).

Simulation design

Person ability is drawn from N(0, 1). Rater severity effects span approximately -0.5 to +0.5 logits. Criterion difficulty effects span approximately -0.3 to +0.3 logits. Scores are generated from the resulting linear predictor plus Gaussian noise, then discretized into four categories. The ⁠_itercal⁠ variants use a second iteration of calibrated rater severity parameters.

Interpreting output

Each dataset is already in long format and can be passed directly to fit_mfrm() after confirming column-role mapping.

Typical workflow

1. Inspect available datasets with list_mfrmr_data().

2. Load one dataset using load_mfrmr_data().

3. Fit and diagnose with fit_mfrm() and diagnose_mfrm().

Source

Simulated for this package with design settings informed by Eckes and Jin (2021).

Examples

data("ej2021_study1", package = "mfrmr")
head(ej2021_study1)
table(ej2021_study1$Study)

mfrmr documentation built on March 31, 2026, 1:06 a.m.