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Add support for EFA/PCA from {psych} package#822

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strengejacke merged 12 commits intomainfrom
strengejacke/issue793
Jun 18, 2025
Merged

Add support for EFA/PCA from {psych} package#822
strengejacke merged 12 commits intomainfrom
strengejacke/issue793

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Fixes #793

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Summary of Changes

Hello @strengejacke, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the performance package's compatibility by integrating support for Factor Analysis and Principal Component Analysis models generated by the psych and parameters packages. Users can now seamlessly apply the package's diagnostic and performance assessment tools, such as normality checks, residual analysis, and model fit evaluation, to these widely used statistical models.

Highlights

  • New Model Support: Extended the performance package's diagnostic capabilities by adding S3 methods for check_normality, check_residuals, and model_performance to support objects from psych::fa(), psych::principal(), and parameters::factor_analysis().
  • Performance Metrics for FA/PCA: Introduced a new model_performance.fa method (also aliased for principal and parameters_efa objects) that extracts key fit indices such as Chi-squared, degrees of freedom, p-value, RMSA, TLI, RMSEA (with confidence intervals), and BIC for Factor Analysis and Principal Component Analysis models.
  • Dependency Management: Updated the DESCRIPTION file to include easystats/insight and easystats/parameters in the Remotes field, ensuring proper dependency resolution for the newly integrated functionalities.
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Code Review

This pull request adds support for EFA/PCA models from the {psych} package and parameters::factor_analysis() objects by implementing check_normality(), check_residuals(), and model_performance() methods. The core logic seems appropriate, but there are critical issues regarding documentation accuracy for model_performance.fa and robustness in handling potentially missing fit statistics from psych::principal objects. Additionally, the NEWS.md entry needs minor corrections for completeness and a typo.

@strengejacke strengejacke merged commit 3506b11 into main Jun 18, 2025
19 of 24 checks passed
@strengejacke strengejacke deleted the strengejacke/issue793 branch June 18, 2025 17:36
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codecov bot commented Jun 18, 2025

Codecov Report

Attention: Patch coverage is 78.57143% with 9 lines in your changes missing coverage. Please review.

Project coverage is 61.90%. Comparing base (98f2f6a) to head (b2c5d44).
Report is 46 commits behind head on main.

Files with missing lines Patch % Lines
R/check_normality.R 50.00% 8 Missing ⚠️
R/test_likelihoodratio.R 83.33% 1 Missing ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##             main     #822      +/-   ##
==========================================
- Coverage   61.90%   61.90%   -0.01%     
==========================================
  Files          89       92       +3     
  Lines        6641     6940     +299     
==========================================
+ Hits         4111     4296     +185     
- Misses       2530     2644     +114     

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Add support for EFA/PCA from {psych} package

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