lavDiag
Latent Variable Models Diagnostics
Description
Diagnostics and visualization tools for latent variable models fitted with 'lavaan' (Rosseel, 2012 <doi:10.18637/jss.v048.i02>). The package provides fast, parallel-safe factor-score prediction (lavPredict_parallel()), data augmentation with model predictions, residuals, delta-method standard errors and confidence intervals (augment()), and model-based latent grids for continuous, ordinal, or mixed indicators (prepare()). It offers item-level empirical versus model curve comparison using generalized additive models for both continuous and ordinal indicators (item_data(), item_plot()) via 'mgcv' (Wood, 2017, ISBN:9781498728331), residual diagnostics including residual correlation tables and plots (resid_cor(), resid_corrplot()) using 'corrplot' (Wei and Simko, 2021 <https://github.com/taiyun/corrplot>), and Q–Q checks of residual z-statistics (resid_qq()), optionally with non-overlapping labels from 'ggrepel' (Slowikowski, 2024 <https://CRAN.R-project.org/package=ggrepel>). Heavy computations are parallelized via 'future'/'furrr' (Bengtsson, 2021 <doi:10.32614/RJ-2021-048>; Vaughan and Dancho, 2018 <https://CRAN.R-project.org/package=furrr>). Methods build on established literature and packages listed above.
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CRAN Check Status
Show all 14 flavors
| Flavor | Status |
|---|---|
| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-macos-arm64 | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
| r-oldrel-macos-x86_64 | OK |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |