projectLSA is an R package that provides a complete graphical user interface (GUI) for conducting Latent Structure Analysis (LSA) through a Shiny application. It integrates multiple latent variable methods, including:
- Latent Profile Analysis (LPA)
- Latent Class Analysis (LCA)
- Latent Trait Analysis (LTA / IRT)
- Exploratory Factor Analysis (EFA)
- Confirmatory Factor Analysis (CFA)
All analyses can be performed without writing any code, making the package accessible for researchers, students, and applied analysts.
# Install from CRAN (when available)
install.packages("projectLSA")
# Install development version from GitHub (optional)
# remotes::install_github("hasandjidu/projectLSA")library(projectLSA)
run_projectLSA()This opens the full Shiny application, including all LSA modules, data upload, built-in datasets, interactive plots, and reporting features.
- Upload your own dataset or use built-in examples.
- Fit multiple LPA models automatically.
- Compare AIC, BIC, entropy, and class size.
- Visualize the best model with customizable class names.
- Supports categorical indicators.
- Fits multiple class solutions.
- Interactive plots with ggiraph.
- Probability tables and class membership export.
- Supports dichotomous and polytomous items.
- Automatically fits Rasch, 2PL, 3PL (or PCM/GRM/GPCM).
- ICC plots, test information, factor scores.
- Multi-dimensional visualization with 3D surfaces and heatmaps.
- KMO, Bartlett test, parallel analysis.
- Factor extraction with rotation.
- Factor scores and loading matrix export.
- Clean HTML summaries for clearer interpretation.
- Lavaan model editor.
- Fit measures, loadings, factor scores.
- Fully customized SEM path diagrams.
If you use projectLSA in publications, please cite:
Djidu, H., Retnawati, H., Hadi, S., & Haryanto (2025). projectLSA: An R Shiny application for latent structure analysis with a graphical user interface.
Bug reports and feature requests are welcome:
https://github.com/hasandjidu/projectLSA/issues
MIT License © 2025 Hasan Djidu