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: | 0.7-22 |
| 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:
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