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$y<-v1*lam1+v2*lam2+v3*lam3+v4*lam4 #change the loading name with the actual loading (number) or extract them from the objectiveML object (they are located in model.sem[[15]]) Note that those loadings are unstandardized and that the resulting variable will not be standardized. Hope it helps Regards, Marko -- Marko Ton?i? Assistant Researcher University of Rijeka Faculty of Humanities and Social Sciences Department of Psychology Sveu?ili?na Avenija 4, 51000 Rijeka, Croatia
"save scores" from sem
2 messages · marKo, John Fox
Dear Marko, I can't quite tell whether this is an original question (as suggested by no "Re:" in the subject field and no text from an earlier message) or an answer to a question already posed (as suggested by the phrasing of the message); if the latter, I apologize for missing the original question. In any event, see the fscore() function in the sem package (?fscore) for computation of factor scores. I hope this helps, John ------------------------------------------------ John Fox Sen. William McMaster Prof. of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ On Mon, 18 Mar 2013 13:21:48 +0100
marKo <mtoncic at ffri.hr> wrote:
I'm not aware of any routine that those the job, although I think that it could be relatively easily done by multiplication the manifest variable vector with the estimates for the specific effect. To make an example: v1; v2; v3; v4 are manifest variables that loads on one y latent variablein a data frame called "A" the code for the model should be like: model <-specifymodel( y -> v1, lam1, NA y -> v2, lam2, NA y -> v3, lam3, NA y -> v4, lam4, NA After fitting the model with sem model.sem <- sem(model, data=A) you should be able to compute the y variable like: attach(data) data$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 Ton?i? Assistant Researcher University of Rijeka Faculty of Humanities and Social Sciences Department of Psychology Sveu?ili?na Avenija 4, 51000 Rijeka, Croatia
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