I'm trying to find a way how to use Factor analysis to improve the separation of two data sets that are measured from the same patients before and after a procedure. The sets both include 100 observations (patients) and seven variables that have two dimensions or factors. If I plot the two data sets first variable against second variable (without factor analysis), I can see a difference between the data sets. But how can I use factor analysis and the two factors (factor scores?) to compare the two data sets?
I was advised to use something called the procrustes rotation to ensure that the two data sets have the same rotation and can be compared. I have never used it, but here's what I did:
A1;%First data set, before procedure. A2;%Second data set, after procedure.
[lambda1,psi1,T1,stats1,F1] = factoran(A1,2);%Default is varimax rotation. [lambda2,psi2,T2,stats2,F2] =factoran(A2,2,'rotate','procrustes','target',lambda1); figure;plot(F1(:,1),F1(:,2),'b.',F2(:,1),F2(:,2),'r+')
It would seem that the distributions are as similar as possible. What am I missing here? Am I supposed to be comparing something else than the factor scores F1 and F2?