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.
Maintainer: Klaus K. Holst klaus@holst.it
Other contributors:
Brice Ozenne [contributor]
Thomas Gerds [contributor]
Klaus K. Holst Maintainer: <klaus@holst.it>
Useful links: