model_performance.fa: Performance of FA / PCA models

In performance: Assessment of Regression Models Performance

Performance of FA / PCA models

Description

Compute indices of model performance for models from the psych package, and for parameters::factor_analysis() and item_omega().

Usage

## S3 method for class 'fa'
model_performance(model, metrics = "all", verbose = TRUE, ...)

Arguments

model	A model object of class fa (e.g., from psych::fa()), principal (e.g., from psych::principal()), or from parameters::factor_analysis() or item_omega().
metrics	Can be "all" or a character vector of metrics to be computed (some of "Chi2", "Chi2_df", "df", "p_Chi2", "RMSA", "RMSA_corrected", "TLI", "RMSEA", and "BIC". For omega-models, can also include "R2" and "Correlation".
verbose	Toggle off warnings.
...	Arguments passed to or from other methods.

Details

For omega-models, the columns R2 and Correlation are measures of factor score adequacy. R2 refers to the multiple R square of scores with factors, while Correlation indicates the correlation of scores with factors.

Value

A data frame (with one row) and one column per "index" (see metrics).

Examples

out <- psych::fa(psychTools::bfi[, 1:25], 5)
model_performance(out)

out <- item_omega(mtcars, n = 3)
model_performance(out)

performance documentation built on Aug. 31, 2025, 1:07 a.m.