OpenMx runs a Two Factor Model but only returns Zero and NA Values
kouros711
Joined: 02/11/2013
| Attachment | Size |
|---|---|
| TwoFactorModel.r | 1.42 KB |
| TwoFactor_Data.dat | 3.66 KB |
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.
summary(congeneric.fit)You had been trying to get the summary of the unfitted model. :)
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In reply to You'll laugh when you see this. by mhunter
Uuuh... that's embarassing.
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In reply to Uuuh... that's embarassing. by kouros711
I've done it dozens of times,
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In reply to I've done it dozens of times, by Ryne
That makes it a bit better,
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In reply to You'll laugh when you see this. by mhunter
workflow: don't change the model name just because it's fitted
m1 = mxRun(m1)
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":
m1 = mxRun(m1)
m2 = mxRun(omxSetParameters(m1, "a1", F,0, name= "dropA"))
m3 = mxRun(omxSetParameters(m2, "a2", F,0, name= "dropA_1_and2"))
mxCompare(m1,c(m2,m3))
otherwise you end up with long statements, and very easily confused words like
greatLongInformativeNameForAModel
greatLongInformativeNameForBModel
Then the informative name is the internal one, which shows up in
.
Your milage may of course vary, I am told.
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