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) <doi:10.1007/s00180-012-0344-y>). 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.

Version: 1.6
Depends: R (≥ 3.0)
Imports: grDevices, graphics, methods, numDeriv, stats, survival, SQUAREM, utils
Suggests: KernSmooth, Matrix, Rgraphviz, ascii, data.table, ellipse, fields, foreach, geepack, gof (≥ 0.9), graph, igraph (≥ 0.6), lava.tobit, lme4, mets (≥ 1.1), optimx, quantreg, rgl, testthat (≥ 0.11), visNetwork, zoo
Published: 2018-01-13
Author: Klaus K. Holst [aut, cre], Brice Ozenne [ctb], Thomas Gerds [ctb]
Maintainer: Klaus K. Holst <klaus at>
License: GPL-3
NeedsCompilation: no
Citation: lava citation info
Materials: NEWS
In views: Psychometrics
CRAN checks: lava results


Reference manual: lava.pdf
Package source: lava_1.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: lava_1.6.tgz
OS X Mavericks binaries: r-oldrel: lava_1.5.1.tgz
Old sources: lava archive

Reverse dependencies:

Reverse depends: lava.tobit, lavaSearch2, mets
Reverse imports: BuyseTest, prodlim, Publish, riskRegression, SmoothHazard, timereg
Reverse suggests: gof, pec, soil.spec


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