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; ), a general Metropolis-Hastings algorithm (amh(); Roberts & Rosenthal, 2001, ) and penalized maximum likelihood estimation (pmle(); Cole, Chu & Greenland, 2014; ).


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")

Reference manual

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install.packages("LAM")

0.7-22 by Alexander Robitzsch, 2 years ago


https://github.com/alexanderrobitzsch/LAM, https://sites.google.com/site/alexanderrobitzsch2/software


Browse source code at https://github.com/cran/LAM


Authors: Alexander Robitzsch [aut,cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports CDM, graphics, Rcpp, sirt, stats, utils

Suggests coda, expm, MASS, numDeriv, TAM

Enhances lavaan, lme4

Linking to Rcpp, RcppArmadillo


Imported by STARTS.


See at CRAN