Pramod Adhikari
> SAS has a VARCLUS procedure (Variable Cluster Analysis) 'to divide a
set of
> variables into nonoverlapping clusters in such a way that each
cluster can
> be interpreted as essentially unidimensional' (Source: SAS
documentation).
> Is there a similar command in STATA that can perform similar
analysis. With
> the existing clustering methods, I can group the variables (after
> transposing observations into variables) using 'generate' command
but the
> standard output from VARCLUS procedure seems easier to interpret.
I can't comment on SAS's procedure, except that the sentence you quote
is
a very strong claim, promising something that in many datasets may be
impossible.
There is a weasel word, "essentially".
If I had a set of continuous variables, then I would explore such
questions in Stata using -pca-. One crux, however, is judging
closeness of
components to variables, for which the correlations between
components and variables are useful information.
In a posting on 28 August, I showed how to do this more
easily using -makematrix- from SSC.
PCA is less appropriate given categorical variables.
Nick
[email protected]
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