lava-package

lava: Latent Variable Models

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) 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) 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. package

Examples

lava()

See Also

Useful links:

• https://kkholst.github.io/lava/
• Report bugs at https://github.com/kkholst/lava/issues

Author(s)

Maintainer : Klaus K. Holst klaus@holst.it

Other contributors:

• Brice Ozenne [contributor]
• Thomas Gerds [contributor]

Klaus K. Holst Maintainer: klaus@holst.it