# Question about PCA

The Statistitxl PCA analysis gives me the '% of Var' at the top of the results page. However, I believe this is the % of Var for PCs of the column X column covariance matrix, while the casewise score PCs are from a row X row covariance matrix. So I believe the '% of Var' does not apply to the 1st 3 casewise scores PCs, and I should transpose the data and re-run the PCA to get the corrext % of Var calculation. However, I'm not sure. Any insight? Sorry if this is confusing - please ask me to clarify if necessary.

## Comments

Anyway, in factor analysis, especially before the development of cluster analysis, it was quite common to use the technique as a means of clustering people rather than finding a way of reducing variables. This technique of inverse factor analysis was called "Q" factor analysis (and the more usual one was called "R" factor analysis.

perhaps you want to carry out an inverted pca something like Q fa? In that case, try looking up Q factor analysis. IIRC it was very popular with political scientists...

Lance

If you are trying to illustrate how much of the variability is explained for each case, I am not sure how you could do this. If you transpose the data and re-run the PCA, then your % of Var will refer to how much of the total variability is explained by case 1, case 2, etc - I don't think that this is what you want.

But, I am not exactly sure what you mean when you say that you "would like to express the percent of explained variance of each of these 3 PCs" - overall, this is the % of Var for the PCA as shown for the original analysis - if you want to somehow do this on a case-by-case basis (i.e. over time) then I am not sure how you could do this.