print.RealVAMS

print.summary.RealVAMS

Prints names of elements in RealVAMS object.

print

Fits a multivariate value-added model (VAM), see Broatch, Green, and Karl (2018) <doi:10.32614/RJ-2018-033> and Broatch and Lohr (2012) <doi:10.3102/1076998610396900>, with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood approach, Wolfinger (1993) <doi:10.1080/00949659308811554>, is used for the estimation of this joint generalized linear mixed model. The inner loop of the pseudo-likelihood routine (estimation of a linear mixed model) occurs in the framework of the EM algorithm presented by Karl, Yang, and Lohr (2013) <DOI:10.1016/j.csda.2012.10.004>. This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.

Andrew T Karl

RealVAMS

Multivariate VAM Fitting

Andrew Karl

Jennifer Broatch

Jennifer Green

print function

<dl> <dt>x</dt>
<dd>object of class RealVAMS</dd> <dt>...</dt>
<dd>other arguments to be passed to summary</dd></dl>

Arguments

Print — print

<dl>

 <dt>x</dt>
<dd>object of class RealVAMS</dd>

 <dt>...</dt>
<dd>other arguments to be passed to summary</dd>

</dl>

print: Print

Description

Usage

Arguments