| lava-package | R Documentation |
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) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s00180-012-0344-y")}). Mixture latent variable models and non-linear latent variable models (Holst and Budtz-Joergensen (2020) \Sexpr[results=rd]{tools:::Rd_expr_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.
A general implementation of Structural Equation Models wth 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.
Maintainer: Klaus K. Holst klaus@holst.it
Authors:
Klaus K. Holst klaus@holst.it
Other contributors:
Benedikt Sommer [contributor]
Brice Ozenne [contributor]
Thomas Gerds [contributor]
Klaus K. Holst Maintainer: klaus@holst.it
Useful links:
Report bugs at https://github.com/kkholst/lava/issues
lava()
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