LAM: Some Latent Variable Models

Includes some procedures for latent variable modeling with a particular focus on multilevel data. The 'LAM' package contains mean and covariance structure modelling for multivariate normally distributed data (mlnormal(); Longford, 1987; <doi:10.1093/biomet/74.4.817>), a general Metropolis-Hastings algorithm (amh(); Roberts & Rosenthal, 2001, <doi:10.1214/ss/1015346320>) and penalized maximum likelihood estimation (pmle(); Cole, Chu & Greenland, 2014; <doi:10.1093/aje/kwt245>).

Version: 0.6-19
Depends: R (≥ 3.1)
Imports: CDM, graphics, Rcpp, sirt, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: coda, expm, MASS, numDeriv, TAM
Enhances: lavaan, lme4
Published: 2022-05-18
DOI: 10.32614/CRAN.package.LAM
Author: Alexander Robitzsch [aut,cre]
Maintainer: Alexander Robitzsch <robitzsch at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: LAM citation info
Materials: README NEWS
In views: Psychometrics
CRAN checks: LAM results


Reference manual: LAM.pdf


Package source: LAM_0.6-19.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): LAM_0.6-19.tgz, r-oldrel (arm64): LAM_0.6-19.tgz, r-release (x86_64): LAM_0.6-19.tgz, r-oldrel (x86_64): LAM_0.6-19.tgz
Old sources: LAM archive

Reverse dependencies:

Reverse imports: STARTS


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