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: 0.4-17
Depends: R (≥ 3.1)
Imports: CDM, graphics, Rcpp, sirt, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: coda, expm, MASS, numDeriv, STARTS, TAM
Enhances: lavaan, lme4
Published: 2019-05-06
Author: Alexander Robitzsch [aut,cre]
Maintainer: Alexander Robitzsch <robitzsch at ipn.uni-kiel.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/alexanderrobitzsch/LAM, https://sites.google.com/site/alexanderrobitzsch2/software
NeedsCompilation: yes
Citation: LAM citation info
Materials: README NEWS
In views: Psychometrics
CRAN checks: LAM results

Downloads:

Reference manual: LAM.pdf
Package source: LAM_0.4-17.tar.gz
Windows binaries: r-devel: LAM_0.4-17.zip, r-devel-gcc8: LAM_0.4-17.zip, r-release: LAM_0.4-17.zip, r-oldrel: LAM_0.4-17.zip
OS X binaries: r-release: LAM_0.4-17.tgz, r-oldrel: LAM_0.4-17.tgz
Old sources: LAM archive

Reverse dependencies:

Reverse imports: STARTS

Linking:

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