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projectLSA  

R Shiny Application for Latent Structure Analysis with a Graphical User Interface
View on CRAN: Click here


Download and install projectLSA package within the R console
Install from CRAN:
install.packages("projectLSA")

Install from Github:
library("remotes")
install_github("cran/projectLSA")

Install by package version:
library("remotes")
install_version("projectLSA", "0.0.6")



Attach the package and use:
library("projectLSA")
Maintained by
Hasan Djidu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-12-10
Latest Update: 2025-12-10
Description:
Provides an interactive Shiny-based toolkit for conducting latent structure analyses, including Latent Profile Analysis (LPA), Latent Class Analysis (LCA), Latent Trait Analysis (LTA/IRT), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). The implementation is grounded in established methodological frameworks: LPA is supported through 'tidyLPA' (Rosenberg et al., 2018) <doi:10.21105/joss.00978>, LCA through 'poLCA' (Linzer & Lewis, 2011), LTA/IRT via 'mirt' (Chalmers, 2012) <doi:10.18637/jss.v048.i06>, and EFA via 'psych' (Revelle, 2025). SEM and CFA functionalities build upon the 'lavaan' framework (Rosseel, 2012) <doi:10.18637/jss.v048.i02>. Users can upload datasets or use built-in examples, fit models, compare fit indices, visualize results, and export outputs without programming.
How to cite:
Hasan Djidu (2025). projectLSA: R Shiny Application for Latent Structure Analysis with a Graphical User Interface. R package version 0.0.6, https://cran.r-project.org/web/packages/projectLSA. Accessed 26 Jun. 2026.
Previous versions and publish date:
0.0.3 (2025-12-10 21:50), 0.0.5 (2026-01-08 21:50), 0.0.6 (2026-01-16 13:00), 0.0.7 (2026-01-30 11:50), 0.0.8 (2026-02-08 00:20)
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Complete documentation for projectLSA
Functions, R codes and Examples using the projectLSA R package
Full projectLSA package functions and examples
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