Scott Colwell
2015-Feb-23 21:33 UTC
[R] Extracting Factor Pattern Matrix Similar to Proc Factor
Thanks David. What do you do when the input is a covariance matrix rather than a dataset? -- View this message in context: http://r.789695.n4.nabble.com/Extracting-Factor-Pattern-Matrix-Similar-to-Proc-Factor-tp4703704p4703719.html Sent from the R help mailing list archive at Nabble.com.
David L Carlson
2015-Feb-23 21:58 UTC
[R] Extracting Factor Pattern Matrix Similar to Proc Factor
Function principal() in psych takes a correlation matrix so use cov2cor() to convert: library(psych) iris.pca <- principal(cov2cor(cov(iris[,-5])), nfactors=4, rotate="none") print(iris.pca$Structure, cutoff=0) David -----Original Message----- From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Scott Colwell Sent: Monday, February 23, 2015 3:34 PM To: r-help at r-project.org Subject: Re: [R] Extracting Factor Pattern Matrix Similar to Proc Factor Thanks David. What do you do when the input is a covariance matrix rather than a dataset? -- View this message in context: http://r.789695.n4.nabble.com/Extracting-Factor-Pattern-Matrix-Similar-to-Proc-Factor-tp4703704p4703719.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
William Revelle
2015-Feb-24 01:03 UTC
[R] Extracting Factor Pattern Matrix Similar to Proc Factor
David and Scott, principal will also take a covariance matrix (set the cover option to TRUE) library(psych) C <- cov(iris[-5]) pc4 <- principal(C,4,covar=TRUE,rotate="none?) However, in the case of no rotation or orthogonal rotations, the structure matrix and the pattern matrix are identical. They differ only if you take an oblique solution. So, pc4 #will give you the results print(pc4$loadings,cutoff=0) #will give the loadings (pattern) print(pc4$Structure,cutoff=0) #will give the structure matrix If the input is a covariance matrix, and you want to do the analysis on the correlation matrix, principal does that automatically. C <- cov(iris[-5]) pc4 <- principal(C,4,rotate="none?) pc4 Bill> On Feb 23, 2015, at 3:58 PM, David L Carlson <dcarlson at tamu.edu> wrote: > > Function principal() in psych takes a correlation matrix so use cov2cor() to convert: > > library(psych) > iris.pca <- principal(cov2cor(cov(iris[,-5])), nfactors=4, rotate="none") > print(iris.pca$Structure, cutoff=0) > > David > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Scott Colwell > Sent: Monday, February 23, 2015 3:34 PM > To: r-help at r-project.org > Subject: Re: [R] Extracting Factor Pattern Matrix Similar to Proc Factor > > Thanks David. What do you do when the input is a covariance matrix rather > than a dataset? > > > > -- > View this message in context: http://r.789695.n4.nabble.com/Extracting-Factor-Pattern-Matrix-Similar-to-Proc-Factor-tp4703704p4703719.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >William Revelle http://personality-project.org/revelle.html Professor http://personality-project.org Department of Psychology http://www.wcas.northwestern.edu/psych/ Northwestern University http://www.northwestern.edu/ Use R for psychology http://personality-project.org/r It is 3 minutes to midnight http://www.thebulletin.org