2014-Jul-31, 20:25:10

Dalliard,

I will reply to most of your criticism later. I am currently visiting my girlfriend in Leipzig and I'm working from my laptop which isn't well-suited for statistical analyses.

However, one point. Yes, it is possible that the 2nd factor is almost the same size as the first. I had actually checked this because I initially did some analyses in SPSS before moving to R (it's my first time using R for a project). Here's what one can do in R:

One will get the 2 factor and 3 factor solutions using max. likelihood. Apparently the first factor is not completely identical across the nfactors to extract, but almost so. ML1 (with nfactors=1) with ML1 from nfactors=2 and 3 was .999.

With nfactors=2, the 2nd factor was much smaller. Var% for ML1 is about 41%, for ML2 it is about 11%,

With 3, ML1=41%, ML2=10%, ML3=5%.

I will reply to most of your criticism later. I am currently visiting my girlfriend in Leipzig and I'm working from my laptop which isn't well-suited for statistical analyses.

However, one point. Yes, it is possible that the 2nd factor is almost the same size as the first. I had actually checked this because I initially did some analyses in SPSS before moving to R (it's my first time using R for a project). Here's what one can do in R:

Code:

`y_ml.2 = fa(y,nfactors=2,rotate="none",scores="regression",fm="ml") #FA with 2 factors`

y_ml.2 #display results

plot(y_ml.2$loadings[1:54],y_ml$loadings) #plots first factors

cor(y_ml.2$loadings[1:54],y_ml$loadings) #correlation ^

y_ml.3 = fa(y,nfactors=3,rotate="none",scores="regression",fm="ml") #same as above just for 3 factors

y_ml.3

plot(y_ml.3$loadings[1:54],y_ml$loadings)

cor(y_ml.3$loadings[1:54],y_ml$loadings)

One will get the 2 factor and 3 factor solutions using max. likelihood. Apparently the first factor is not completely identical across the nfactors to extract, but almost so. ML1 (with nfactors=1) with ML1 from nfactors=2 and 3 was .999.

With nfactors=2, the 2nd factor was much smaller. Var% for ML1 is about 41%, for ML2 it is about 11%,

With 3, ML1=41%, ML2=10%, ML3=5%.