I'm not aware of any routine that those the job, although I think that
it could be relatively easily done by multiplication the manifest
variable vector with the estimates for the specific effect.
To make an example:
v1; v2; v3; v4 are manifest variables that loads on one y latent
variablein a data frame called "A"
the code for the model should be like:
model <-specifymodel(
y -> v1, lam1, NA
y -> v2, lam2, NA
y -> v3, lam3, NA
y -> v4, lam4, NA
After fitting the model with sem
model.sem <- sem(model, data=A)
you should be able to compute the y variable like:
attach(data)
data$y<-v1*lam1+v2*lam2+v3*lam3+v4*lam4 #change the loading name with
the actual loading (number) or extract them from the objectiveML object
(they are located in model.sem[[15]])
Note that those loadings are unstandardized and that the resulting
variable will not be standardized.
Hope it helps
Regards,
Marko
--
Marko Tončić
Assistant Researcher
University of Rijeka
Faculty of Humanities and Social Sciences
Department of Psychology
Sveučilišna Avenija 4, 51000 Rijeka, Croatia
______________________________________________
[email protected] mailing list
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.
