[R] Error in structural equation model - "The model has negativedegrees of freedom"
jfox at mcmaster.ca
Thu Dec 1 14:59:27 CET 2005
There are 7*8/2 = 28 raw moments among the 7 observed variables. Of these,
6*7/2 = 21 are used for the moments among the 6 fixed-exogenous variables,
leaving 28 - 21 = 7 df. You model has 11 free parameters. So df for the
model = 11 - 7 = -4.
Some additional comments:
If you're using raw moments, why isn't there a constant variable in the
Do you really intend x1 -- x6 to be causes, rather than indicators, of m1
Why are there no normalizing constraints on the latent variables?
Do you really want to fit a model like this to so small a data set?
I hope this helps,
Department of Sociology
Canada L8S 4M4
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Sunil W
> Sent: Wednesday, November 30, 2005 10:08 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] Error in structural equation model - "The model
> has negativedegrees of freedom"
> I am running a structural equation model with R using the sem
> command; am getting the following error:
> "Error in sem.default : The model has negative degrees of
> freedom = -4"
> My model is as follows:
> s_model = specify.model()
> x1->m1, b1,NA
> x2->m1, b2,NA
> x3->m2, b3,NA
> x4->m2, b4,NA
> x5->m2, b5,NA
> x6->m2, b6,NA
> m1->y, a1,NA
> m2->y, a2,NA
> m1<->m1, v1,NA
> m2<->m2, v2,NA
> y<->y, v3,NA
> x1-x6 are observed independent variables, m1 and m2 are the
> latent variables and y is the observed dependent variable. I
> use the raw.moments command for calculating the covariance
> matrix, based on a data with 147 observations.
> The command that I use is as follows:
> s = sem(s_model,S=R,obs.variables=colnames(R),
> fixed.x=c('x1','x2','x3','x4','x5','x6'), raw=TRUE)
> I would appreciate any help on this; I am new to structural
> equation models
> and realize that I may be making a silly error.
> R-help at stat.math.ethz.ch mailing list
> PLEASE do read the posting guide!
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