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<h1 align="center">
Orthomax Rotation of a PCA model </h1>

<p style="text-align: justify;">
<font size="2">In factor analysis rotations of the loadings are very often 
applied, whereas in chemometrics these methods are very seldom used. This is in 
spite of the fact that it is possible to obtain better conditions for 
interpretation of PCA models on complex data.<br>
<br>
</font><font size="2">We here provide an algorithm by which it is possible to 
apply rotations from the Orthomax family (quartimax and varimax) to a PCA-model.
</font> </p>
<p>
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<p class="MsoNormal" style="text-align: center;" align="center">
&nbsp;</p>
<p class="MsoNormal" style="text-align: center;" align="center">
<i><span lang="en-us"><font size="2">Back-transformed loadings corresponding to 
the first twelve components derived from a PCA model based on 1H NMR spectra of 
24 preparations of St. John抯 wort. (A) and the corresponding rotated PCA model 
(loadings rotated) (B). The score plot of the sixth and seventh component of the 
rotated PCA model shows a tight clustering of preparations (C). </font></span>
</i>
<span style="font-size: 10pt;" lang="EN-US">&nbsp;</span></p>
<p class="MsoNormal" align="left">&nbsp;<br>
<font size="2">The above figure shows how rotations can make complex loadings 
much simpler, and thus easier to interpret. The example clearly illustrates how 
interpretation of the influence of a specific compound on the observed 
clustering is facilitated using the rotated loadings (B) as compared to the 
non-rotated loadings (A). Interpretation is aided since the influence of this 
compound on the observed clustering is partitioned over many components in the 
non-rotated PCA model, whereas in the rotated PCA model the influence is 
described mainly by the sixth and seventh components. A score plot of the sixth 
and seventh component of the rotated PCA model is shown in C. The plot shows, 
that the clustering of preparation 3 in the positive direction of the seventh 
component is due only to higher levels of the specific compound as compared with 
other preparations. <br>
<br>
The example shows an example of rotation of loadings, but it is also possible to 
rotate the scores. This can be particularly useful when you want simpler 
conditions for understanding the influence of variables on the clustering of 
individual samples.<br>
<br>
<br>
<br>
Download:</font></p>

<blockquote>
  <ul>
    <li>
<span lang="en-us">
<a href="http://www.models.kvl.dk/intranet/dl-monitor/go.asp?get=mf.m" style="text-decoration: none;">
<font size="2">Rotation function</font></a><font size="2"> (uses PLS_Toolbox)</font></span></li>
  </ul>
</blockquote>


<p><font size="2">Please refer to the below paper when using the function:</font></p>


<p><font size="2">A Juul Lawaetz, B Schmidt, D St鎟k, JW Jaroszewski, R Bro, 
Application of rotated PCA models to metabolite profiles to facilitate 
interpretation: Commercial preparations of St. John's wort, Journal of 
Chemometrics, Submitted</font></p>
<p>&nbsp;</p>




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    Last edited: 
    Monday, January 14, 2008 8:20:29 PM
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