I can't think of a quicker way to make a variable off-hand but I am sure if one exists, Nick Cox knows it.
As to the way you reverse the signs, all you need to do is reflect the variable, i.e., multiply by -1. This is best done by making new variables which you use in your analysis, keeping the old ones around for reference.
gen myvarflip = -1*myvar
This is a good idea if you have variables worded in a negative and positive direction.
Depending on what the variable is, you may want to shift it too. Let's say the original responses are between 1 and 5. Then
gen myvarnew = 6 - myvar
preserves the original response scale but flips everything around.
You are free to reflect and recenter because PCA only cares about covariances and variances. (The fact that it cares about variances is the essential difference between PCA and factor analysis, which eliminates the variances and uses only off-diagonal information.) While reflecting a variable alters the covariances, it does so in a predictable fashion.
If you are doing PCA on a correlation matrix, you might as well standardize everything and reflect the variables to a convenient direction before analysis.
In statistical inference a correlation matrix and a covariance matrix differ, because you made the correlation matrix by dividing by random variables (the variances and geometric means of standard deviations), but I doubt this is of much interest and I don't think -pca- corrects for this difference when it spits out statistics. Perhaps I am incorrect, though---check the manual.
-----Original Message-----
From: [email protected]
To: "[email protected]" <[email protected]>
Sent: 1/10/2009 6:26 PM
Subject: st: generating new var using principal components eigen
Dear STATA list,
I am trying to create a single var_simple comprised of the sum of var*pc1 (pc1 is the score of component one of a principle components analysis). I have tried a simple formula where var_simple= pc1*var1+ pc1*var2 etc... but thought there must be a quicker way to compute this that I am unaware of. Also, in the first example, I obtained a number of negative values (some of the var's had a negative score for pc1) and I was wanting to transform them into positive values in simple_var. Any help would be greatly appreciated Thanks for your attention to what is no doubt a simple problem!
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