Latent Variable Models R package lava version 1.9.2 CRAN Task View: Psychometrics (https://CRAN.R-project.org/view=Psychometrics) 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. Software Depends: R (>= 3.5.0) Imports: cli, future.apply, graphics, grDevices, methods, numDeriv, progressr, stats, survival, SQUAREM, utils Suggests: KernSmooth, Rgraphviz, data.table, ellipse, fields, future, geepack, graph, knitr, rmarkdown, igraph (>= 0.6), lavaSearch2, lme4 (>= 1.1.35.1), MASS, Matrix (>= 1.6.3), mets (>= 1.1), nlme, optimx, polycor, quantreg, rgl, svglite, targeted (>= 0.4), testthat (>= 0.11), vdiffr, visNetwork Klaus K. Holst <klaus@holst.it> Comprehensive R Archive Network (CRAN) Klaus K. Holst [aut, cre], Benedikt Sommer [ctb], Brice Ozenne [ctb], Thomas Gerds [ctb] Apache License (== 2.0) 2026-06-30 application/tgz https://CRAN.R-project.org/package=lava doi:10.32614/CRAN.package.lava