lamle

Approximate marginal maximum likelihood estimation of multidimensional latent variable models via adaptive quadrature or Laplace approximations to the integrals in the likelihood function, as presented for confirmatory factor analysis models in Jin, S., Noh, M., and Lee, Y. (2018) doi:10.1080/10705511.2017.1403287, for item response theory models in Andersson, B., and Xin, T. (2021) doi:10.3102/1076998620945199, and for generalized linear latent variable models in Andersson, B., Jin, S., and Zhang, M. (2023) doi:10.1016/j.csda.2023.107710. Models implemented include the generalized partial credit model, the graded response model, and generalized linear latent variable models for Poisson, negative-binomial and normal distributions. Supports a combination of binary, ordinal, count and continuous observed variables and multiple group models.

Last 30 days

This package has been downloaded 148 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 1,857 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jan 21, 2025 with 24 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.