You can indeed fit confirmatory factor analysis models with the sem package, and ?sem includes an example of a second-order CFI (though I'm not sure I see the point of factor-analyzing uncorrelated variables). In factor analysis, moreover, the observed variables are functions of the factors, not vice-versa (which is how you've specified it). As well, you have to define variances and possibly covariances for the factors.
You'll find a simpler example in some lecture notes at <http://socserv.socsci.mcmaster.ca/jfox/Courses/soc761/index.html#lecture-notes>, along with the corresponding sem commands.
I hope that this helps, John
At 01:21 AM 1/29/2004 +0000, Arnab mukherji wrote:
Hi
Has anyone used R to conduct confirmatory factor analysis? This email pertains to use of SEM.
For context consider an example: the basic idea is that there are a bunch of observables variables (say study habbits, amount of time reading in the bus, doing homework, helping other do homework, doing follow-up on errors etc.) and one believes that all these variables maybe measured by two or more unobservable constructs... say ability to work hard and ability to follow instructions. If one has empirical evidence from earlier studies which relates similar observable to similar unobservables one wants to do a confirmatory factor analysis to check if the posited relationship holds in the current data being analyzed.
I thought the way out would be to use SEM - the structural equation model library. However, i am not sure how to estimate SEM objects where factors are unobservable. The only discussion pertian to the case of endogenously detemined observable variables.
here is a test case of what i'd like to implement
#example Measurement Model
x1<-runif(200) x2<-rbinom(200, 20, 0.75) x3<-runif(200) x4<-runif(200) dat<-as.data.frame(x1 =x1, x2 = x2, x3 = x3, x4 = x4)
v.c<-cor(dat,use = "complete.obs") ind<-upper.tri(v.c) v.c[ind]<-0 model.dhp<-matrix (c( "x1 -> HWK", "gam11", NA, "x2 -> HWK", "gam21", NA, "x2 -> FI", "gam22", NA, "x3 -> HWK", "gam31", NA, "x3 -> F1", "gam32", NA, "x4 -> F1", "gam42", NA), ncol = 3, byrow = TRUE) These are the Factor loadings i'd like to test for: variable HWK FI x1 0.75 0 x2 0.20 0.68 x3 0.2 0.5 x4 0 0.24
thanks for any help on this.
Arnab
----------------------------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario, Canada L8S 4M4 email: [EMAIL PROTECTED] phone: 905-525-9140x23604 web: www.socsci.mcmaster.ca/jfox
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