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: 0.7-22 Depends: R (≥ 3.1) Imports: CDM, graphics, Rcpp, sirt, stats, utils LinkingTo: Rcpp, RcppArmadillo Suggests: coda, expm, MASS, numDeriv, TAM Enhances: lavaan, lme4 Published: 2024-07-15 DOI: 10.32614/CRAN.package.LAM 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 Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=LAM to link to this page.
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