plot.im_mst

Conditional Maximum Likelihood Calibration and data management of multistage tests.
Supports polytomous items and incomplete designs with linear as well as multistage tests.
Extended Nominal Response and Interaction models, DIF and profile analysis.
See Robert J. Zwitser and Gunter Maris (2015)<doi:10.1007/s11336-013-9369-6>.

Timo Bechger

dexterMST

CML and Bayesian Calibration of Multistage Tests

Jesse Koops

Ivailo Partchev

Gunter Maris

Robert Zwitser

plot.im_mst function

<dl><dt>x</dt>
<dd>output of <code>fit_inter_mst</code></dd>
<dt>item_id</dt>
<dd>id of the item to plot</dd>
<dt>show.observed</dt>
<dd>plot the observed mean item scores for each test score</dd>
<dt>curtains</dt>
<dd>percentage of most extreme values to cover with curtains, 0 to omit curtains</dd>
<dt>zoom</dt>
<dd>if TRUE, limits the plot area to the test score range allowed by the routing rules</dd>
<dt>...</dt>
<dd>further arguments to plot</dd></dl>

Arguments

plots for the interaction model — plot.im_mst

<dl>

<dt>x</dt>
<dd>output of <code>fit_inter_mst</code></dd>


<dt>item_id</dt>
<dd>id of the item to plot</dd>


<dt>show.observed</dt>
<dd>plot the observed mean item scores for each test score</dd>


<dt>curtains</dt>
<dd>percentage of most extreme values to cover with curtains, 0 to omit curtains</dd>


<dt>zoom</dt>
<dd>if TRUE, limits the plot area to the test score range allowed by the routing rules</dd>


<dt>...</dt>
<dd>further arguments to plot</dd>

</dl>

plots for the interaction model

plot.im_mst: plots for the interaction model

Description

Usage

Arguments