On 06/09/2011 06:06 PM, R Help wrote:
I am using missing = 'fiml', which would require estimating intercepts.
I figured they would effect my overall model fit, but can I still
estimate my loading coefficients the same way?
Yes, no problem.
Yves Rosseel
http://lavaan.org
_
On 06/09/2011 05:21 PM, R Help wrote:
Ok, I think this is the last question I have. My model is producing
an estimate of intercepts for my variables along with my loadings.
From the documentation it appears that this is controlled by the
meanstructure option in cfa. It says that setting it t
I am using missing = 'fiml', which would require estimating intercepts.
I figured they would effect my overall model fit, but can I still
estimate my loading coefficients the same way?
The warning would be helpful, but if I had looked closer into the
'fiml' option I might have been able to figure
Ok, I think this is the last question I have. My model is producing
an estimate of intercepts for my variables along with my loadings.
>From the documentation it appears that this is controlled by the
meanstructure option in cfa. It says that setting it to TRUE includes
the intercepts, and sett
Thanks for the help, the std.lv=TRUE command is exactly what I was
looking for. As you stated, it doesn't matter in terms of overall
model fit, but my client is more interested in the loadings than the
factor variances.
In terms of speed, it's just a very large model (7 factors, 90
observations,
On 06/08/2011 11:56 PM, R Help wrote:
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?
If you have a latent variable in your model (like a factor in CFA), yo
Dear Sam,
> -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 5:57 PM
> To: John Fox
> Cc: r-help
> Subject: Re: [R] Results of CFA with Lavaan
>
> Yes, that is the difference
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 r
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 var
What do you mean by latent estimate?
The table of variances has variances for each factors.
Is there something different in the sem output that you don't see here?
Yes, this looks normal.
Jeremy
On 8 June 2011 13:14, R Help wrote:
> I've just found the lavaan package, and I really apprecia
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