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.
Package details |
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| Author | Klaus K. Holst [aut, cre], Benedikt Sommer [ctb], Brice Ozenne [ctb], Thomas Gerds [ctb] |
| Maintainer | Klaus K. Holst <klaus@holst.it> |
| License | Apache License (== 2.0) |
| Version | 1.10 |
| URL | https://kkholst.github.io/lava/ https://github.com/kkholst/lava |
| Package repository | View on CRAN |
| Installation |
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