On Wed, 2006-08-16 at 08:47 -0400, John Fox wrote: > Dear Rick, > > There are a couple of problems here: > > (1) You've fixed the error variance parameters for each of the observed > variables to 1 rather than defining each as a free parameter to estimate. > For example, use > > X1 <-> X1, theta1, NA > > Rather than > > X1 <-> X1, NA, 1 > > The general principle is that if you give a parameter a name, it's a free > parameter to be estimated; if you give the name as NA, then the parameter is > given a fixed value (here, 1). (There is some more information on this and > on error-variance parameters in ?sem.) > > (2) I believe that the model you're trying to specify -- in which all > variables but X6 load on F1, and all variables but X1 load on F2 -- is > underidentified. > > In addition, you've set the metric of the factors by fixing one loading to > 0.20 and another to 0.25. That should work but strikes me as unusual, and > makes me wonder whether this was what you really intended. It would be more > common in a CFA to fix the variance of each factor to 1, and let the factor > loadings be free parameters. Then the factor covariance would be their > correlation. > > You should not have to specify start values for free parameters (such as > g11, g22, and g12 in your model), though it is not wrong to do so. I would > not, however, specify start values that imply a singular covariance matrix > among the factors, as you've done; I'm surprised that the program was able > to get by the start values to produce a solution. > > BTW, the Thurstone example in ?sem is for a confirmatory factor analysis > (albeit a slightly more complicated one with a second-order factor). There's > also an example of a one-factor CFA in the paper at > <http://socserv.socsci.mcmaster.ca/jfox/Misc/sem/SEM-paper.pdf>, though this > is for ordinal observed variables. > > I hope this helps, > John > > -------------------------------- > John Fox > Department of Sociology > McMaster University > Hamilton, Ontario > Canada L8S 4M4 > 905-525-9140x23604 > http://socserv.mcmaster.ca/jfox > --------------------------------
Thanks for the information. I think I understand how to handle the residual variance after reading the sem help file more carefully. Now I have to figure out how to constrain each column of the factor matrix to sum to one. Maybe this will fix the problem with being under-identified. Rick B. ______________________________________________ R-help@stat.math.ethz.ch 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.