prints

print.center

print.ICCm

print.rsqmlm

print.varCompare

Prints for <code>mlmtools</code> objects

Multilevel models (mixed effects models) are the statistical tool of choice for analyzing multilevel data (Searle et al, 2009). These models account for the correlated nature of observations within higher level units by adding group-level error terms that augment the singular residual error of a standard OLS regression. Multilevel and mixed effects models often require specialized data pre-processing and further post-estimation derivations and graphics to gain insight into model results. The package presented here, 'mlmtools', is a suite of pre- and post-estimation tools for multilevel models in 'R'. Package implements post-estimation tools designed to work with models estimated using 'lme4''s (Bates et al., 2014) lmer() function, which fits linear mixed effects regression models. Searle, S. R., Casella, G., & McCulloch, C. E. (2009, ISBN:978-0470009598). Bates, D., Mächler, M., Bolker, B., & Walker, S. (2014) <doi:10.18637/jss.v067.i01>.

Laura Jamison

mlmtools

Multi-Level Model Assessment Kit

Laura Jamison 

Jessica Mazen 

Erik Ruzek 

Gus Sjobeck 

prints function

<dl><dt>x</dt>
<dd>Object from <code>mlmtools</code> package</dd>
<dt>...</dt>
<dd>Additional arguments</dd></dl>

Arguments

S3Methods for Printing — prints

<dl>

<dt>x</dt>
<dd>Object from <code>mlmtools</code> package</dd>


<dt>...</dt>
<dd>Additional arguments</dd>

</dl>

S3Methods for Printing

prints: S3Methods for Printing

Description

Usage

Value

Arguments