Results of CFA with Lavaan

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of R Help
Sent: June-08-11 5:57 PM
To: John Fox
Cc: r-help
Subject: Re: [R] Results of CFA with Lavaan

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 <jfox at 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-bounces at r-project.org
[mailto:r-help-bounces at 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