iterPlot

Plot parameter estimates at each <code><a href="/link/optim?package=PLmixed&version=0.1.7" data-mini-rdoc="PLmixed::optim">optim</a></code> iteration.

glmm

GLLAMM

Utilizes the 'lme4' and 'optimx' packages (previously the optim()
function from 'stats') to estimate (generalized) linear mixed models (GLMM)
with factor structures using a profile likelihood approach, as outlined in
Jeon and Rabe-Hesketh (2012) <doi:10.3102/1076998611417628> and
Rockwood and Jeon (2019) <doi:10.1080/00273171.2018.1516541>.
Factor analysis and item response models can be extended to allow
for an arbitrary number of nested and crossed random effects,
making it useful for multilevel and cross-classified models.

Nicholas Rockwood

PLmixed

Estimate (Generalized) Linear Mixed Models with Factor
Structures

Minjeong Jeon

iterPlot function

<dl><dt>object</dt>
<dd>an object of class PLmod</dd></dl>

Arguments

Plot parameter estimates at each <code><a href='https://rdrr.io/r/stats/optim.html'>optim</a></code> iteration.

iterPlot — iterPlot

<dl>

<dt>object</dt>
<dd>an object of class PLmod</dd>

</dl>

iterPlot: iterPlot

Description

Usage

Arguments