Fit Indices PreviousNext
Mplus Discussion > Structural Equation Modeling >
Message/Author
 Anthony S. Boyce posted on Wednesday, March 28, 2007 - 3:02 pm
A colleague and I both recently ran the same model on the same data, I used MPlus and he used LISREL. Our models were identical although the chi-square values differed by 2.0 and some of the estimates differed by less than .01. However, the CFI and TLI indices were substantially different (i.e., MPLUS: CFI=.73, TLI=.72; LISREL: CFI=.89, TLI/NNFI=.88). Do you have any idea why the fit indices would be so different?

Thanks very much for any help you can provide.
 Linda K. Muthen posted on Thursday, March 29, 2007 - 8:40 am
I suspect that your model has covariates. In this case, the baseline model differs between LISREL and Mplus. The baseline model in LISREL does not contain covariances among the covariates. In Mplus, it does.
 laura smith posted on Friday, February 01, 2008 - 2:25 pm
hello:

i am a beginner to SEM and to Mplus, so thanks in advance for your patience.

my question is: can fit indices be too high? initially, i ran the measurement portion of my model and obtained a nonsignificant chi-square (good) but a CFI of .88, a TLI of .65, and an RMSEA of .25 (not so good).

next, as one of the model modification indices was theoretically consistent with my model, i added it (it was a WITH path). Consequently, the last three fit indices improved dramatically(CFI=1, TLI=1, RMSEA=0).

The model is not just-identified, but it has only one degree of freedom. could that be the "problem" that is creating a near-perfect model fit?

also, as i went on to the structural model, the degree of freedom increased, but the fit indices remained at those high levels.

i would like to be happy about the seemingly excellent fit of this model, but it seems suspicious to me. can you suggest some factors that i should investigate to see whether they are inflating these indices spuriously?

thanks so much! this discussion board is a treasure.
 Linda K. Muthen posted on Friday, February 01, 2008 - 2:52 pm
It sounds like the correlations among your observed variables are low. This makes it difficult to reject the H0 model. And with only one degree of freedom, the model does not place many restrictions on the H1 model. You may also have a small sample size which results in low power.
 laura smith posted on Saturday, February 02, 2008 - 10:22 am
thanks very much for those pointers, linda.

looking into those possibilities, my sample size is 321, which i think is reasonable.

the correlations among the 4 indicators of the proposed latent range from .61 to .34 (with three of them below .40 at .39, .39, and .34).

do those sound low enough to you to suggest that i've found where the problem may lie?

thanks once again...
 Linda K. Muthen posted on Monday, February 04, 2008 - 8:49 am
Your correlations don't sound that low and your sample size is not particularly large. But with one degree of freedom, you don't have many restrictions. If you send two outputs, one without the WITH statement and one where the WITH statement dramatically changes the fit, and your license number to support@statmodel.com, I can take a look at it.
 Lauree Tilton-Weaver posted on Monday, April 21, 2008 - 10:31 am
If you have a fully saturated model, is it a good idea to add another variable (say a control), so that you have fit indices that are meaningful?
 Linda K. Muthen posted on Monday, April 21, 2008 - 10:48 am
This does not make sense to me.
 Lauree Tilton-Weaver posted on Monday, April 21, 2008 - 12:51 pm
Okay - I'm looking at someone else's model - it's fully saturated (they're looking at mediation)...and saying that the fit indices can't be evaluated, I'm assuming because of the saturation. I just wondered if there wasn't something that could be done to make the fit indices meaningful, rather than just leaving it at that.
 Linda K. Muthen posted on Monday, April 21, 2008 - 4:49 pm
A saturated model has perfect fit. It is only when there are restrictions on the model that fit can be assessed.
 Lauree Tilton-Weaver posted on Tuesday, April 22, 2008 - 6:04 am
That's part of my point/question. If it has perfect fit because it's saturated, does it make sense to just leave it at that? They've tested a mediation model, and have two control variables with the exogenous, outcomes, and mediators all controlled. I can't see where a constraint would make sense. But it seems strange to just say "it's saturated, we can't evaluate model fit."
 Linda K. Muthen posted on Tuesday, April 22, 2008 - 8:29 am
You can't evaluate model fit but you can evaluate whether the indirect effect is significant. Perhaps that is sufficient.
 Rob Nobel posted on Tuesday, November 11, 2008 - 1:23 am
Hi,

I was wondering: is the term saturated a "discrete" term (is a model only saturated with df=0) or can you also say that a model with for example df=1 is "highly saturated" and thus that fit indices are less informative?
 Linda K. Muthen posted on Wednesday, November 12, 2008 - 8:14 am
In my experience a saturated model is a model with no degrees of freedom. I have never seen a discussion of degrees of saturation.
 Sandra posted on Thursday, March 20, 2014 - 8:51 am
Hi,

I am conducting a CFA on my own, and I am not sure about my chi-square and RMSEA:


Chi-square test of Model fit: 2777.516 and p <.000
(I have 295 participants in this analysis, can I consider this a large sample size to justify a non-significant result?)

RMSEA estimate= .044
90% C.I. = .041 .047
P-value = .999
(RMSEA is lower than .06 however it is not significant, how should I interpret this result?)

CFI = .86
(not good but near)

SRMR = .058
(good)


The modification indices suggest relationships that do not make sense theoretically...

Also how can I know that a variable is problematic for my factor?

Many thanks in advance!
 Linda K. Muthen posted on Thursday, March 20, 2014 - 1:35 pm
With such a small sample, you cannot discount chi-square. I would say the model does not fit.

EFA is a good way to isolate a problematic variable. See the Topic 1 course handout and video on the website for further information.
Back to top
Add Your Message Here
Post:
Username: Posting Information:
This is a private posting area. Only registered users and moderators may post messages here.
Password:
Options: Enable HTML code in message
Automatically activate URLs in message
Action: