search for: oblimin

A bit of a newbee to R and factor rotation I am trying to understand factor rotations and their implementation in R, particularly the GPArotation library. I have tried to reproduce some of the examples that I have found, e.g., I have taken the values from Jacksons example in "Oblimin Rotation", Encyclopedia of Biostatistics http://onlinelibrary.wiley.com/doi/10.1002/0470011815.b2a13060/abstract and run it through R: library(GPArotation) data <- matrix(c(0.6, 0.39, 0.77, 0.70, 0.64, 0.35, 0.52, 0.72, 0.34, 0.58, 0.15, 0.07, -0.13, -0.23, -0.23, 0.67, -0.27, -0.23, 0.7...

...simple way to do the following, but i haven't been able to find it. I am hoping a merciful soul on R-help could point me in the right direction. I am doing a factor analysis on survey data with missing values. to do this, I run: FA1<-factanal(na.omit(DATA), factors = X, rotation = 'oblimin', scores = 'regression') Now that I have my factors and factor scores, I want to add those scores back to my original dataset so I can plot factor scores by demographics. However, when I try to add the scores back to the original data frame, the variables are of different lengths....

...radient Projection Algorithms and Software for Arbitrary Rotation Criteria in Factor Analysis, ", Educational and Psychological Measurement (in press). Additional details are available on the web site <http://www.stat.ucla.edu/research/gpa>. The following rotations are available: oblimin oblique oblimin family quartimin oblique targetT orthogonal target rotation targetQ oblique target rotation pstT orthogonal partially specified target rotation pstQ oblique partially specified target rota...

...radient Projection Algorithms and Software for Arbitrary Rotation Criteria in Factor Analysis, ", Educational and Psychological Measurement (in press). Additional details are available on the web site <http://www.stat.ucla.edu/research/gpa>. The following rotations are available: oblimin oblique oblimin family quartimin oblique targetT orthogonal target rotation targetQ oblique target rotation pstT orthogonal partially specified target rotation pstQ oblique partially specified target rota...

I am running a PCA, but would like to rotate my data and limit the number of factors that are analyzed. I can do this using the "principal" command from the psych package [principal(my.data, nfactors=3,rotate="varimax")], but the issue is that this does not report scores for the Principal Components the way "princomp" does. My question is: Can you get an

Dear R-List, I have carried out a factor analysis using fa (psych) with nfactors=2, rotation="oblimin" and fm="pa". Now I have to report both pattern AND structure matrix. As I have understood R-Documentation, this can be obtained by setting the "oblique.scores" argument TRUE (structure matrix) or FALSE (pattern matrix), respectively. However both produced the same loading...