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...gt; 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 Ton?i? Assistant Researcher University of Rijeka Faculty of Humanities and Social Sciences Department of...

...have 2 factors (F3 and F4), and also F1 and F2 are nested within F3. Here is the code that I have, but it is giving me an error message "Warning message: In eval(expr, envir, enclos) : Negative parameter variances. Model may be underidentified." and a further error "Error in summary.objectiveML(cfa, fit.indices = c("NNFI", "CFI", "RMSEA")) : coefficient covariances cannot be computed". I have run CFA before with no issues. This is the first time I am running a nested model. Any help will be greatly appreciated. Regards, Mat cov.matrix<-cov(na.omit(df)...

Hi, I'm trying to perform a hierachical, second order CFA. That's the thing that I need to leave AMOS. I found some sim.hierarchical and omega stuff, but nothing clear enough. Can anyone help me? I just need a simple and clear manual. Best, Pablo. [[alternative HTML version deleted]]

Hi R-help, I am using the sem package to run confirmatory factor analysis (cfa) on some questionnaire data collected from 307 participants. I have been running R-2.15.3 in Windows in conjunction with R studio. The model I am using was developed from exploratory factor analysis of a separate dataset (n=439); it includes 18 items that load onto 3 factors. I have used the sem package documentation