Latent Variable Models
conda install odsp-test::r-lavaconda install odsp-test/label/abs::r-lavaconda install odsp-test/label/abs-r::r-lavaconda install odsp-test/label/abs-r2::r-lavaconda install odsp-test/label/ptf_2019_q3::r-lavaconda install odsp-test/label/q2_fail::r-lavaconda install odsp-test/label/r-essentials::r-lavaconda install odsp-test/label/r-lang::r-lavaconda install odsp-test/label/test::r-lava
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) <>). Mixture latent variable models and non-linear latent variable models (Holst and Budtz-Joergensen (2019) <>). 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.