Description
Some Latent Variable Models.
Description
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>).
README.md
LAM
Some Latent Variable Models
If you use LAM and have suggestions for improvement or have found bugs, please email me at [email protected]. Please always provide a minimal dataset, necessary to demonstrate the problem, a minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and all necessary information on the used librarys, the R version, and the OS it is run on, perhaps a sessionInfo().
Manual
The manual may be found here https://alexanderrobitzsch.github.io/LAM/
CRAN version
The official version of LAM is hosted on CRAN and may be found here. The CRAN version can be installed from within R using:
utils::install.packages("LAM")
GitHub version
The version hosted here is the development version of LAM. The GitHub version can be installed using devtools as:
devtools::install_github("alexanderrobitzsch/LAM")