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 Travis Salway Hottes posted on Tuesday, January 19, 2016 - 11:04 am
Hello,

I am a new Mplus user--thanks for any help or advice!

I'm trying to run a measurement model + multiple paths (SEM). I've pasted my model syntax below. There are 8,037 observations (no missing data). The outcome (o1) is binary; I'm using ESTIMATOR = ML. I have three latent variables (f1, f2, f3), and all of my indicators are binary (a1-a16) or ordinal/categorical (b1-b9, c1-c5). I am testing 4 different measured mediators (m1-m4), and I have 6 measured covariates (x1-x6).

I have two questions:

1. MPlus has been running for almost 2 hours now. I'm wondering if this is usual--perhaps given the complexity, number of dimensions in my model--or if I need to adjust any settings to help the model converge?

2. Are there any issues with combining binary indicators (latent variable f1) and ordinal indicators (latent variables f2 and f3)? E.g., would the interpretation of the coefficients change for these different factors?

Thanks,
Travis

MODEL: f1 BY a1-a16;
f2 BY b1-b9;
f3 BY c1-c5;
o1 ON f1 f2 f3 m1-m4 x1-x6;
m1 ON f1 f2 f3 x1-x6;
m2 ON f1 f2 f3 x1-x6;
m3 ON f1 f2 f3 x1-x6;
m4 ON f1 f2 f3 x1-x6;
f1 ON x1-x6;
f2 ON x1-x6;
f3 ON x1-x6;
 Bengt O. Muthen posted on Tuesday, January 19, 2016 - 11:22 am
1. How many dimensions of integration did your screen printing say that you have?

2. No problem doing this. The coefficients are in the logit scale so your interpretations of them are in line with logistic regression.
 Travis Salway Hottes posted on Tuesday, January 19, 2016 - 11:52 am
Hi,

Thank you for your reply. The screen printing says I have 3 dimensions of integration.
 Bengt O. Muthen posted on Tuesday, January 19, 2016 - 6:22 pm
That's 15*15*15 = 3375 integration points which shouldn't be too bad if you have several processors (like 8) - but it does get slower with many observations like you have.

If you have a slow computer you can try

integration = montecarlo(500);

but keep an eye on TECH8 to make sure you don't get negative ABS changes due poor precision. 1000 points should still take only a third of the time.
 Travis Salway Hottes posted on Wednesday, January 20, 2016 - 10:06 am
I'm a student & am running the analysis on my own laptop, which has 1 processor (dual core), so perhaps this explains the long running time.

I tried your suggestion with the integration=montecarlo(500) command. This reduced the running time from 4.5 hours to 1 hour.

I did check the TECH8 output. The ABS change was negative after the sixteenth step. Can you tell me how to interpret this? I also noticed that while most of the coefficients are approximately the same, some were fairly different.

Thank you for your help.
 Bengt O. Muthen posted on Wednesday, January 20, 2016 - 7:24 pm
Negative ABS changes are a sign of numerical imprecision, which is in turn due to a small number of integration points (500 here). Increase to 1000 and see how that comes out.

But you could use a faster computer for these sorts of analyses.

Also, Bayesian estimation may be faster.
 Travis Salway Hottes posted on Thursday, January 21, 2016 - 8:08 pm
I'll give it a try. Thank you again for your help.
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