HI, I am testing several models about three latent constructs that measure risk attitudes. Two models with different structure obtained identical of fit measures from chisqure to BIC. Model1 assumes three factors are correlated with each other and model two assumes a higher order factor exist and three factors related to this higher factor instead of to each other. Model1: model.one <- specify.model() tr<->tp,e.trtp,NA tp<->weber,e.tpweber,NA weber<->tr,e.webertr,NA weber<->weber, e.weber,NA tp<->tp,e.tp,NA tr <->tr,e.trv,NA .... Model two model.two <- specify.model() rsk->tp,e.rsktp,NA rsk->tr,e.rsktr,NA rsk->weber,e.rskweber,NA rsk<->rsk, NA,1 weber<->weber, e.weber,NA tp<->tp,e.tp,NA tr <->tr,e.trv,NA .... the summary of both sem model gives identical fit indices, using same data set. is there some thing wrong with this mode specification? Thanks
Dear hyena,> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]On> Behalf Of hyena > Sent: March-14-09 5:07 PM > To: r-help at stat.math.ethz.ch > Subject: [R] SEM model testing with identical goodness of fits > > HI, > > I am testing several models about three latent constructs that > measure risk attitudes. > Two models with different structure obtained identical of fit measures > from chisqure to BIC. > Model1 assumes three factors are correlated with each other and model > two assumes a higher order factor exist and three factors related to > this higher factor instead of to each other. > > Model1: > model.one <- specify.model() > tr<->tp,e.trtp,NA > tp<->weber,e.tpweber,NA > weber<->tr,e.webertr,NA > weber<->weber, e.weber,NA > tp<->tp,e.tp,NA > tr <->tr,e.trv,NA > .... > > Model two > model.two <- specify.model() > rsk->tp,e.rsktp,NA > rsk->tr,e.rsktr,NA > rsk->weber,e.rskweber,NA > rsk<->rsk, NA,1 > weber<->weber, e.weber,NA > tp<->tp,e.tp,NA > tr <->tr,e.trv,NA > .... > > the summary of both sem model gives identical fit indices, using same > data set. > > is there some thing wrong with this mode specification?>From your verbal description, I would have thought that the second model ismore restrictive than the first, but that doesn't seem to be the case -- if the two models have identical log-likelihoods and degrees of freedom, as you seem to imply, then it's a good bet that the models are observationally indistinguishable. On the other hand, you don't provide a whole lot of information; it would have been much more informative had you shown the input and output for both models. John> > Thanks > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
Dear hyena, Actually, looking at this a bit more closely, the first models dedicate 6 parameters to the correlational and variational structure of the three variables that you mention -- 3 variances and 3 covariances; the second model also dedicates 6 parameters -- 3 factor loadings and 3 error variances (with the variance of the factor fixed as a normalization). You don't show the remaining structure of the models, but a good guess is that they are observationally indistinguishable. John> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]On> Behalf Of hyena > Sent: March-14-09 5:07 PM > To: r-help at stat.math.ethz.ch > Subject: [R] SEM model testing with identical goodness of fits > > HI, > > I am testing several models about three latent constructs that > measure risk attitudes. > Two models with different structure obtained identical of fit measures > from chisqure to BIC. > Model1 assumes three factors are correlated with each other and model > two assumes a higher order factor exist and three factors related to > this higher factor instead of to each other. > > Model1: > model.one <- specify.model() > tr<->tp,e.trtp,NA > tp<->weber,e.tpweber,NA > weber<->tr,e.webertr,NA > weber<->weber, e.weber,NA > tp<->tp,e.tp,NA > tr <->tr,e.trv,NA > .... > > Model two > model.two <- specify.model() > rsk->tp,e.rsktp,NA > rsk->tr,e.rsktr,NA > rsk->weber,e.rskweber,NA > rsk<->rsk, NA,1 > weber<->weber, e.weber,NA > tp<->tp,e.tp,NA > tr <->tr,e.trv,NA > .... > > the summary of both sem model gives identical fit indices, using same > data set. > > is there some thing wrong with this mode specification? > > Thanks > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.