-----------------------------------
Dear Sunil,
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 model?
Do you really intend x1 -- x6 to be causes, rather than indicators, of
m1 and m2?
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,
John
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox
-----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"
Hi
I am running a structural equation model with R using the
am getting the following error:
"Error in sem.default : The model has negative degrees of
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,
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.