# PLmixed

The purpose of `PLmixed`

is to extend the capabilities of
`lme4`

to allow factor structures (i.e., factor loadings and
discrimination parameters) to be freely estimated. Thus, factor analysis
and item response theory models with multiple hierarchical levels and/or
crossed random effects can be estimated using code that requires little
more input than that required by `lme4`

. All of the strengths
of `lme4`

, including the ability to add (possibly random)
covariates and an arbitrary number of crossed random effects, are
encompassed within `PLmixed`

. In fact, `PLmixed`

uses `lme4`

and `optim`

to estimate the model
using nested maximizations. Details of this approach can be found in
Jeon and Rabe-Hesketh (2012). A manuscript documenting the use of
`PLmixed`

is currently in preparation.

## Installation

`PLmixed`

can be installed from CRAN with:

`install.packages("PLmixed")`