[R] Bayesian PCA

[William Revelle]

Dear Lucy,
   You might consider some of the scale construction techniques 
available in the psych package.  In particular, the iclust function 
is meant for this very problem:  how to form reliable item composites.

Bill

At 4:38 PM +0100 4/12/11, Christian Hennig wrote:
>Dear Lucy,
>
>not an R-related response at all, but if it's questionnaire data, 
>I'd probably try to do dimension reduction in a non-automated way by 
>defining a number of 10 or so meaningful scores that summarise your 
>questions.
>Dimension reduction is essentially about how to aggregate the given 
>information into low-dimensional measurements, which according to my 
>opinion should be rather driven by the research aim and meaning of 
>the variables than by the distribution of the data, if at all 
>possible.
>You can then use PCA in order to examine the remaining dimensions
>
>Christian
>
>On Tue, 12 Apr 2011, Lucy Asher wrote:
>
>>First of all I should say this email is more of a general 
>>statistics questions rather than being specific to using R but I'm 
>>hoping that this may be of general interest.
>>
>>I have a dataset that I would really like to use PCA on and have 
>>been using the package pcaMethods to examine my data. The results 
>>using traditional PCA come out really nicely. The dataset is 
>>comprised of a set of questions on dog behaviour answered by their 
>>handlers. The questions fall into distinct components which may 
>>biological sense and the residuals are reasonable small. Now the 
>>problem. I don't have a big enough sample to run traditional PCA. I 
>>have about 40 dogs and 60 questions so which ever way you look at 
>>it not enough. There is past data available on some of the 
>>questions and the realtionships between them so I was wondering 
>>whether Bayesian PCA would be a useful alternative using past 
>>research to inform my priors. I wondered if anyone knew whether 
>>Bayesian PCA was better suited to smaller datasets than traditional 
>>(ML) PCA? If not I wondered if anyone knew of packages in R that 
>>could do dimension reduction on datasets with small sample sizes?
>>
>>Many Thanks,
>>
>>Lucy
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>
>*** --- ***
>Christian Hennig
>University College London, Department of Statistical Science
>Gower St., London WC1E 6BT, phone +44 207 679 1698
>chrish at stats.ucl.ac.uk, www.homepages.ucl.ac.uk/~ucakche
>
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-- 
William Revelle		http://personality-project.org/revelle.html
Professor			http://personality-project.org
Department of Psychology             http://www.wcas.northwestern.edu/psych/
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