A general implementation of Structural Equation Modelswith latent variables (MLE, 2SLS, and composite likelihoodestimators) with both continuous, censored, and ordinaloutcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>).Mixture latent variable models and non-linear latent variable models(Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>).The package also provides methods for graph exploration (d-separation,back-door criterion), simulation of general non-linear latent variablemodels, and estimation of influence functions for a broad range ofstatistical models.
| Version: | 1.8.2 |
| Depends: | R (≥ 3.0) |
| Imports: | cli,future.apply, graphics, grDevices, methods,numDeriv,progressr, stats,survival,SQUAREM, utils |
| Suggests: | KernSmooth,Rgraphviz,data.table,ellipse,fields,geepack,graph,knitr,rmarkdown,igraph (≥ 0.6),lavaSearch2,lme4 (≥1.1.35.1),MASS,Matrix (≥ 1.6.3),mets (≥ 1.1),nlme,optimx,polycor,quantreg,rgl,targeted (≥ 0.4),testthat (≥0.11),visNetwork |
| Published: | 2025-10-30 |
| DOI: | 10.32614/CRAN.package.lava |
| Author: | Klaus K. Holst [aut, cre], Brice Ozenne [ctb], Thomas Gerds [ctb] |
| Maintainer: | Klaus K. Holst <klaus at holst.it> |
| BugReports: | https://github.com/kkholst/lava/issues |
| License: | GPL-3 |
| URL: | https://kkholst.github.io/lava/ |
| NeedsCompilation: | no |
| Citation: | lava citation info |
| Materials: | README,NEWS |
| In views: | Psychometrics |
| CRAN checks: | lava results |