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<table width="100%" summary="page for plot.pmatrix.class"><tr><td>plot.pmatrix.class</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>
Plot pmatrix.class objects
</h2>

<h3>Description</h3>

<p>S3 Method to <code>plot</code> objects of class pmatrix.class.
Graphic display of the checks of pmatrix. 
One graph for each item plotting the rows of the P(++) matrix and rows of the P(&ndash;) matrix.
If nonintersection holds the lines in the plots of the P(++) matrix must be nondecreasing
and the lines in the plots of the P(&ndash;) matrix nust be nonincreasing.
</p>


<h3>Usage</h3>

<pre>
## S3 method for class 'pmatrix.class'
plot(x, items = all.items, pmatrix = "both", ci = TRUE, 
              alpha = .05, color = "black", transparancy = 20, ask = TRUE, ...)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>x</code></td>
<td>
<p>Object of class pmatrix.class produced by <code>check.pmatrix</code>.</p>
</td></tr>
<tr valign="top"><td><code>items</code></td>
<td>
<p>vector containing the numbers of the item pairs for which the results are depicted graphically.
Default the results for all items are depicted.</p>
</td></tr>
<tr valign="top"><td><code>pmatrix</code></td>
<td>
<p>Valid options are <code>"ppp"</code>, <code>"pmm"</code>, and <code>"both"</code>.
If <code>pmatrix="ppp"</code>, then the P(++) matrix is plotted,
if <code>pmatrix="pmm"</code>, then the P(&ndash;) matrix is plotted,
if <code>pmatrix="both"</code>, then both the P(++) matrix and P(&ndash;) matrix are plotted.</p>
</td></tr>
<tr valign="top"><td><code>ci</code></td>
<td>
<p>Boolean. If <code>TRUE</code>, then confidence envelops are plotted around IRFs and ISRFs.</p>
</td></tr>              
<tr valign="top"><td><code>alpha</code></td>
<td>
<p>Type of plotted (1 - alpha) confidence intervals. By default 95-percent confidence intervals are depicted</p>
</td></tr>
<tr valign="top"><td><code>color</code></td>
<td>
<p>Color of the plotted curves and confidence envelops. Default is black.</p>
</td></tr>
<tr valign="top"><td><code>transparancy</code></td>
<td>
<p>Transparancy of the confidence intervals. Higher values result in more opaque colors for the confidence intervals.</p>
</td></tr> 
<tr valign="top"><td><code>ask</code></td>
<td>
<p>Boolean. If <code>TRUE</code> (default), then <code>par("ask"=TRUE)</code>; i.e., a hard return between subsequent plots is required.
If <code>FALSE</code>, then <code>par("ask"=FALSE)</code>.</p>
</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
<p>Optional graphical parameters will be ignored</p>
</td></tr>  
</table>


<h3>Details</h3>

<p>The default graphic device in R may only display the last graph.
</p>
<p>In the plot of the P(++) matrix and the P(&ndash;) matrix, the x-axis 
contains the <i>k =(J-1)m</i> item steps not pertaining to item j in order of popularity (ascending).
Let <i>Y_g=1</i> indicate that the g-th item step has been taken: i.e. <i>Xi &ge;q  y</i>
and let <i>Y_g=0</i> indicate that the g-th item step has not been taken: i.e. <i>Xi &lt;  y</i>.
The <i>m</i> lines in the plot of the P(++) matrix connect <i>P(X_j &ge;q x, Y_1=1), &hellip;, P(X_j &ge;q x, Y_k=1)), x = 1, &hellip; m</i>.
The <i>m</i> lines in the plot of the P(&ndash;) matrix connect <i>P(X_j &lt; x, Y_1=0), &hellip;, P(X_j &lt; x, Y_k=0)), x = 1, &hellip;, m</i>.
</p>
<p>If the number of item steps on the x-axis is greater than 10, then the labels are not displayed,
</p>


<h3>Value</h3>

<p>Returns a graph.
</p>


<h3>Author(s)</h3>

<p>L. A. van der Ark <a href="mailto:L.A.vanderArk@uva.nl">L.A.vanderArk@uva.nl</a>
</p>


<h3>References</h3>

<p>Molenaar, I.W., &amp; Sijtsma, K. (2000) 
<em>User's Manual MSP5 for Windows</em> [Software manual].
IEC ProGAMMA.
</p>
<p>Sijtsma, K., &amp; Molenaar, I. W. (2002)
<em>Introduction to nonparametric item response theory</em>.
Sage.
</p>
<p>Van der Ark, L. A. (2007). 
Mokken scale analysis in <span class="pkg">R</span>. 
<em>Journal of Statistical Software</em>.
\Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("10.18637/jss.v020.i11")}
</p>


<h3>See Also</h3>

<p><code>check.pmatrix</code>, <code>summary.pmatrix.class</code>
</p>


<h3>Examples</h3>

<pre>
data(acl)
Communality &lt;- acl[,1:10]
pmatrix.list &lt;- check.pmatrix(Communality)
plot(pmatrix.list)
summary(pmatrix.list)
</pre>


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