A general implementation of Structural Equation Models
with latent variables (MLE, 2SLS, and composite likelihood
estimators) with both continuous, censored, and ordinal
outcomes (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 variable
models, and estimation of influence functions for a broad range of
statistical models.
| Version: |
1.7.1 |
| Depends: |
R (≥ 3.0) |
| Imports: |
future.apply, grDevices, graphics, methods, numDeriv, progressr, stats, survival, SQUAREM, utils |
| Suggests: |
KernSmooth, Matrix, Rgraphviz, data.table, ellipse, fields, geepack, graph, knitr, bookdown, rmarkdown, igraph (≥ 0.6), lavaSearch2, lme4, mets (≥ 1.1), nlme, optimx, polycor, quantreg, rgl, R.rsp (≥ 0.40), targeted (≥ 0.2), testthat (≥
0.11), visNetwork, zoo |
| Published: |
2023-01-06 |
| 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 |