Yes, that is the difference. For the last SEM I built I fixed the factor variances to 1, and I think that's what I want to do for the CFA I'm doing now. Does that make sense for a CFA?
I'll try figuring out how to do that with lavaan later, but my model takes so long to fit that I can't try it right now. Thanks, Sam On Wed, Jun 8, 2011 at 5:58 PM, John Fox <j...@mcmaster.ca> wrote: > Dear Sam, > > In each case, the first observed variable is treated as a "reference > indicator" with its coefficient fixed to 1 to establish the metric of the > corresponding factor and therefore to identify the model. If you didn't do > the same thing (or something equivalent, such as fixing the factor variances > to 1) in specifying the model to sem::sem(), that might account for the > problems you encountered. > > Best, > John > > -------------------------------- > John Fox > Senator William McMaster > Professor of Social Statistics > Department of Sociology > McMaster University > Hamilton, Ontario, Canada > http://socserv.mcmaster.ca/jfox > > > >> -----Original Message----- >> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] >> On Behalf Of R Help >> Sent: June-08-11 4:15 PM >> To: r-help >> Subject: [R] Results of CFA with Lavaan >> >> I've just found the lavaan package, and I really appreciate it, as it >> seems to succeed with models that were failing in sem::sem. I need some >> clarification, however, in the output, and I was hoping the list could >> help me. >> >> I'll go with the standard example from the help documentation, as my >> problem is much larger but no more complicated than that. >> >> My question is, why is there one latent estimate that is set to 1 with >> no SD for each factor? Is that normal? When I've managed to get >> sem::sem to fit a model this has not been the case. >> >> Thanks, >> Sam Stewart >> >> HS.model <- ' visual =~ x1 + x2 + x3 >> textual =~ x4 + x5 + x6 >> speed =~ x7 + x8 + x9 ' >> fit <- sem(HS.model, data=HolzingerSwineford1939) summary(fit, >> fit.measures=TRUE) Lavaan (0.4-8) converged normally after 35 iterations >> >> Number of observations 301 >> >> Estimator ML >> Minimum Function Chi-square 85.306 >> Degrees of freedom 24 >> P-value 0.000 >> >> Chi-square test baseline model: >> >> Minimum Function Chi-square 918.852 >> Degrees of freedom 36 >> P-value 0.000 >> >> Full model versus baseline model: >> >> Comparative Fit Index (CFI) 0.931 >> Tucker-Lewis Index (TLI) 0.896 >> >> Loglikelihood and Information Criteria: >> >> Loglikelihood user model (H0) -3737.745 >> Loglikelihood unrestricted model (H1) -3695.092 >> >> Number of free parameters 21 >> Akaike (AIC) 7517.490 >> Bayesian (BIC) 7595.339 >> Sample-size adjusted Bayesian (BIC) 7528.739 >> >> Root Mean Square Error of Approximation: >> >> RMSEA 0.092 >> 90 Percent Confidence Interval 0.071 0.114 >> P-value RMSEA <= 0.05 0.001 >> >> Standardized Root Mean Square Residual: >> >> SRMR 0.065 >> >> Parameter estimates: >> >> Information Expected >> Standard Errors Standard >> >> >> Estimate Std.err Z-value P(>|z|) Latent variables: >> visual =~ >> x1 1.000 >> x2 0.554 0.100 5.554 0.000 >> x3 0.729 0.109 6.685 0.000 >> textual =~ >> x4 1.000 >> x5 1.113 0.065 17.014 0.000 >> x6 0.926 0.055 16.703 0.000 >> speed =~ >> x7 1.000 >> x8 1.180 0.165 7.152 0.000 >> x9 1.082 0.151 7.155 0.000 >> >> Covariances: >> visual ~~ >> textual 0.408 0.074 5.552 0.000 >> speed 0.262 0.056 4.660 0.000 >> textual ~~ >> speed 0.173 0.049 3.518 0.000 >> >> Variances: >> x1 0.549 0.114 4.833 0.000 >> x2 1.134 0.102 11.146 0.000 >> x3 0.844 0.091 9.317 0.000 >> x4 0.371 0.048 7.778 0.000 >> x5 0.446 0.058 7.642 0.000 >> x6 0.356 0.043 8.277 0.000 >> x7 0.799 0.081 9.823 0.000 >> x8 0.488 0.074 6.573 0.000 >> x9 0.566 0.071 8.003 0.000 >> visual 0.809 0.145 5.564 0.000 >> textual 0.979 0.112 8.737 0.000 >> speed 0.384 0.086 4.451 0.000 >> >> ______________________________________________ >> R-help@r-project.org 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. > > ______________________________________________ R-help@r-project.org 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.
