Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
RE: st: How to implement Discrete Principal Component Analysis by using POLYCHORICPCA
From
Cameron McIntosh <[email protected]>
To
STATA LIST <[email protected]>
Subject
RE: st: How to implement Discrete Principal Component Analysis by using POLYCHORICPCA
Date
Thu, 5 Jan 2012 15:38:35 -0500
What's the purpose here? You want to compare two ways of doing PCA with discrete variables? Doesn't the polychoric pca module give you all you need to know?Cam
> Date: Fri, 6 Jan 2012 00:26:50 +0400
> Subject: st: How to implement Discrete Principal Component Analysis by using POLYCHORICPCA
> From: [email protected]
> To: [email protected]
>
> Dear all,
>
> Happy New year.
>
> Is there anyone who knows how to implement Discrete Principal
> Component Analysis after running POLYCHORICPCA.ado. My question is
> that, after obtaining the eigenvalues, how can I know the
> corresponding eigenvector which is similar to those eigenvector
> obtained after running PCA procedure, shown below.
>
>
> Principal components (eigenvectors)
>
> ------------------------------------------------
> Variable | Comp1 Comp2 | Unexplained
> -------------+--------------------+-------------
> foreign | 0.7071 0.7071 | 0
> gear_ratio | 0.7071 -0.7071 | 0
> ------------------------------------------------
>
> Thank you very much for your help in advance.
> with kind regards,
>
>
> Charles Wang
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/