Model fit indices for a logistic regr...
Message/Author
 Nicole Watkins posted on Friday, August 30, 2019 - 7:40 am
Hello,
I am trying to conduct a multiple group logistic regression, and I am getting weird model fit statistics. Is my model underidentified?

Here is the input:

VARIABLE:
USEVARIABLES ARE
y1 x1 x2 x3 x4 x5 x6 x7 x8
x9 x78 x79;

CATEGORICAL = y1;
MISSING IS .;
GROUPING = x1(0=male 1=female);

ANALYSIS:
ITERATIONS = 100000;
MODEL:

y1 ON x1 x2 x3 x4 x5 x6 x7 x8
x9 x78 x79;

And here is some of the output:

MODEL FIT INFORMATION

Number of Free Parameters 22

Chi-Square Test of Model Fit

Value 0.000*
Degrees of Freedom 0
P-Value 0.0000

Chi-Square Contribution From Each Group

MALE 0.000
FEMALE 0.000
RMSEA (Root Mean Square Error Of Approximation)

Estimate 0.000
90 Percent C.I. 0.000 0.000
Probability RMSEA <= .05 0.000

CFI/TLI

CFI 1.000
TLI 1.000
 Bengt O. Muthen posted on Saturday, August 31, 2019 - 5:33 pm
This model is "just-identified" so that no overall model test of fit is available. You can test if there is gender equality. The way your model is now written, you let males and females have different estimates.
 Nicole Watkins posted on Friday, September 06, 2019 - 12:05 pm
Dr. Muthen,
I am interested specifically in the path y1 ON x78. x1-x5 are control variables in the analysis and I do not have any theoretical reason as to why they should be unconstrained. Should I then, in service of having a more parsimonious model, have the paths y1 ON x1-x5 constrained, and then compare the model that also constrains the y1 on x78 path? I disagree with a colleague on this topic. I believe that I should constrain the control variable path but they believe I should leave it unconstrained and only try constraining the path I am interested in and test the difference. Is there a good article/book that would walk through this sort of decision?