title: standardization of data in R
body: <p>I am doing some PCA analysis for large spreadsheets, and I'm picking my PCs according to the loadings.
  As far as I have read, since the data I have have differnt units, standardization is a must before performing the PCA analysis.</p>
  
  <p>Does the function <code>prcomp()</code> inherently performs standardization?</p>
  
  <p>I was reading the <code>prcomp()</code> help file and saw this under the arguments of <code>prcomp()</code>:</p>
  
  <pre><code>scale. a logical value indicating whether the variables should be scaled to have
         unit variance before the analysis takes place. The default is FALSE for 
         consistency with S, but in general scaling is advisable. Alternatively, a
         vector of length equal the number of columns of x can be supplied. The
         value is passed to scale.
  </code></pre>
  
  <p>Does "scaling variables to have unit variance" mean standardization?</p>
  
  <p>I am currently using this command:</p>
  
  <pre><code>prcomp(formula = ~., data=file, center = TRUE, scale = TRUE, na.action = na.omit)
  </code></pre>
  
  <p>is it enough? or shall I do a separate step of standardization?</p>
  
  <p>Thanks,</p>