When I do an EFA from the package psych I can generate really nice path plots with correlations and loadings and such like this:
using the fa.diagram function with the following code:
library(psych)
covariances <- ability.cov$cov
correlations <- cov2cor(covariances)
fa.promax <- fa(correlations, nfactors=2, rotate="promax", fm="pa")
fa.diagram(fa.promax, simple=FALSE)
I tend to use CFA more than EFA and would like to be able to plot the model with correlations in the same way. I use the SEM package. I have tried the pathDiagram function but it only produces the code that I can then paste to GVedit from Graphviz. I do that and the correlations and between factor correlations aren't there. Additionally I don't like cutting and pasting to another program (though the help file from sem for pathDiagram reads: "To obtain graphics output directly, the dot program must be on the system search path."; I don't know what exactly to put in the path to make that happen and if it will even have the correlations anyway?)
I'd like to be able to make a path diagram similar to what fa.diagram from psych does for EFA. I'd like to be able to do this in R and not cut and paste. I don't care what package you use to do this but I think most people would agree the simpler the better and if it can be done within R it would give great freedom of the choice of graphics device.
Here is some sample code for a CFA model to work with:
dat3 <- read.table(url("http://dl.dropbox.com/u/61803503/Proj_2b.dat"),
header=T, strip.white = T, as.is=FALSE,
na.strings= c("999", "NA", " "))
NHSDA.cov <- cov(dat3)
ete.mod <- specifyModel()
F1 -> item3, lam1, NA
F1 -> item5, lam2, NA
F1 -> item9, lam3, NA
F1 -> item10, lam4, NA
F2 -> item4, lam5, NA
F2 -> item13, lam6, NA
F2 -> item14, lam7, NA
F2 -> item15, lam8, NA
F3 -> item1, lam9, NA
F3 -> item6, lam10, NA
F3 -> item7, lam11, NA
F3 -> item11, lam12, NA
F3 -> item12, lam13, NA
F4 -> item2, lam14, NA
F4 -> item8, lam15, NA
F4 -> item16, lam16, NA
F4 -> item17, lam17, NA
item1 <-> item1, e1, NA
item2 <-> item2, e2, NA
item3 <-> item3, e3, NA
item4 <-> item4, e4, NA
item5 <-> item5, e5, NA
item6 <-> item6, e6, NA
item7 <-> item7, e7, NA
item8 <-> item8, e8, NA
item9 <-> item9, e9, NA
item10 <-> item10, e10, NA
item11 <-> item11, e11, NA
item12 <-> item12, e12, NA
item13 <-> item13, e13, NA
item14 <-> item14, e14, NA
item15 <-> item15, e15, NA
item16 <-> item16, e16, NA
item17 <-> item17, e17, NA
F1 <-> F1, NA, 1
F2 <-> F2, NA, 1
F3 <-> F3, NA, 1
F4 <-> F4, NA, 1
F2 <-> F1, rF1F2 #1
F3 <-> F1, rF1F3 #2
F4 <-> F1, rF1F4 #3
F3 <-> F2, rF2F3 #4
F4 <-> F2, rF2F4 #5
F4 <-> F3, rF3F4 #6
ete.sem <- sem(ete.mod, NHSDA.cov, nrow(dat3))
(ete.SUM <- summary(ete.sem))
pathDiagram(ete.sem) #the attempt thus far
Running R 2.14.2 on Win 7
