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Mplus Discussion > Latent Variable Mixture Modeling >
 Anonymous posted on Friday, September 05, 2003 - 11:28 am
I am new to latent class analysis and I'm trying to running a 2 class model with 1 dichotomous and 3 3-category variables. I'm not sure how to specify the starting values for the thresholds. I tried putting in some numbers ranging from -2 to 2. However, I keep getting an error message that says: "IN THE OPTIMIZATION, ONE OR MORE LOGIT THRESHOLDS APPROACHED AND WERE SET AT THE EXTREME VALUES. EXTREME VALUES ARE -15.000 AND 15.000." I've tried putting in different values, but have not been able to fix the problem.

I'd appreciate any suggestions about what might be the source of the problem and how to fix it.

Thank you!
 Linda K. Muthen posted on Monday, September 08, 2003 - 6:34 pm
This is not a problem. It just means that in certain classes, certain items have either a probability of zero or one. This can help define the classes.
 Jonathan Larson posted on Friday, June 07, 2013 - 8:14 am
We tried to change the reference class in a latent class analysis by entering starting values for the thresholds, but the reference class did not change. Even when we tried using extreme starting values the reference class did not change. We only succeeded by constraining the thresholds with the @ symbol. Do you know why this might have happened?

Thank you very much for your help!
 Linda K. Muthen posted on Friday, June 07, 2013 - 9:50 am
Do you have STARTS=0;

You may find using the STARTS option of the OUTPUT command useful. This gives the input with starting values and you can simply change the class numbers.
 Jonathan Larson posted on Tuesday, November 12, 2013 - 10:54 am
We had random starts, but using STARTS = 0 solved the problem. Thanks for your help!
 DavidBoyda posted on Sunday, March 04, 2018 - 7:34 am
Hi Professor,

I have regressed my LCA classes onto two distal outcomes, however, one of the variables has low observations (<30 cases).

When examining the thresholds for said distal outcomes one of the variables across two classes has high fixed thresholds:

Y2$1 15.000 0.000 999.000 999.000

I understand this is because there is (almost) nobody in the highest category of Y2 in that class.

Is there any function within Mplus that i can call to get around this? Or is it normal to report this?
 Bengt O. Muthen posted on Sunday, March 04, 2018 - 2:21 pm
You don't want to get around this; just report it. It is useful to know that membership in a certain class determines the distal outcome category.

A comment on nomenclature - you don't regress classes onto a distal. You regress a distal onto the classes.
 DavidBoyda posted on Tuesday, March 13, 2018 - 9:56 am
Dear Bengt,

in reference to my enquiry above your answer (March 04)

Y2$1 15.000 0.000 999.000 999.000

could you provide a little more clarity on what you said:

"...It is useful to know that membership in a certain class determines the distal outcome category".

My classes were mental health and distal outcome is suicide. So, are you saying, there were suicide attempts in class 1 but no attempts in the other classes and this is a function of class endorsement?

kind regards,

 Bengt O. Muthen posted on Tuesday, March 13, 2018 - 11:28 am
If Y2 is a binary distal, the Y2$1 15.000 result for a certain class implies that when a person is in this class there is zero probability of being in the highest category of the distal. The fact that the probability is zero and not for instance 0.25 (greater than zero, not ignorable, but not close to 1 or even 0.5) makes the relationship between the latent class and the distal stronger.
 DavidBoyda posted on Thursday, March 29, 2018 - 7:03 am
Dear Professor,

regarding the final step of the manual 3step and a binary distal outcome, how would I present the Mplus output considering they are thresholds? Would I say that the thresholds for suicide in class 1 was XYZ with a small probablity (0.011) of endorsing the highest category?

Y2$1 4.514 0.709 6.367 0.000
Y3$1 1.703 0.235 7.246 0.000


Latent Class 1

Category 1 0.989 0.008 130.197 0.000
Category 2 0.011 0.008 1.426 0.154
Category 1 0.846 0.031 27.611 0.000
Category 2 0.154 0.031 5.031 0.000
 Bengt O. Muthen posted on Thursday, March 29, 2018 - 12:20 pm
Yes, you can say that. Or, simply report only the probability results.
 Tasseli McKay posted on Wednesday, February 13, 2019 - 12:52 am
Hello, I’m trying to get predicted values for females on a model developed on their male partners. I used the SVALUES option of the OUTPUT command in the male model output and applied these values to fix the estimates when fitting the model to female data. However, I get the following error: "One or more pairs of ordered thresholds are not increasing in Class 1."

I assume the underlying issue is that not all of the threshold estimates in the male model results are increasing, e.g.:

M0THREAT$1 3.859 0.743 5.194 0.000
M0THREAT$2 1.987 0.635 3.131 0.002
M0THREAT$3 1.251 0.519 2.410 0.016
M0THREAT$4 0.661 0.424 1.560 0.119

But the Mplus website states that “…threshold values are always increasing…”. Could you help me understand how to address this error so I can fit the male model to the female data?
 Linda K. Muthen posted on Wednesday, February 13, 2019 - 6:43 am
Please send the output and your license number to
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