Attachment | Size |
---|---|
TwoFactorModel.r | 1.42 KB |
TwoFactor_Data.dat | 3.66 KB |
Hi,
I'm trying to reproduce an analysis of a congeneric two- factor- model from a textbook and I can't figure out where I am going wrong. The model has two latent factors (selfevaluation and foreignevaluation scales) with three indicators each. The output I get looks like this:
> summary(congeneric)
free parameters:
[1] lbound ubound
<0 Zeilen> (oder row.names mit Länge 0)
observed statistics: 0
estimated parameters: 0
degrees of freedom: 0
-2 log likelihood: NA
saturated -2 log likelihood: NA
number of observations: 0
chi-square: NA
p: NA
Information Criteria:
df Penalty Parameters Penalty Sample-Size Adjusted
AIC: NA NA NA
BIC: NA NA NA
CFI: NA
TLI: NA
RMSEA: NA
timestamp: NULL
frontend time: NULL
backend time: NULL
independent submodels time: NULL
wall clock time: NULL
cpu time: NULL
openmx version number: NULL
I have tried all sorts of modifications to my code, but nothing helped. It seems like I must be overlooking something terribly important. I would really appreciate some help! I attached my code and the data.
Jens
You'll laugh when you see this. Try
summary(congeneric.fit)
You had been trying to get the summary of the unfitted model. :)
summary(congeneric)
Uuuh... that's embarassing. Well, thank you for your help!
I've done it dozens of times, as has everyone else on the development team. Welcome, you're one of us!
That makes it a bit better, that it happened to you, too:-) Thanks for the warm welcome and for this forum!
For this reason I always do
i.e., don't change the model name just because it's fitted. This makes for far fewer errors, and captures a strength of openMx, which is that a "model is a fit is a model"
I also don't tend to use the
paradigm.
When you're in a workflow, I just use a short generic model name like "m1":
otherwise you end up with long statements, and very easily confused words like
Then the informative name is the internal one, which shows up in
.
Your milage may of course vary, I am told.