Predicted value of HLM ordinal logist... PreviousNext
Mplus Discussion > Categorical Data Modeling >
 Jessica Li posted on Thursday, July 03, 2014 - 11:06 am
How do I get/calculate the predicted value of an outcome in a multilevel ordinal logistic regression? Even outside Mplus. Where are the intercepts?

Estimate S.E. Est./S.E. P-Value
Within Level
C1 -0.011 0.014 -0.816 0.414
C2 -0.063 0.099 -0.635 0.525
C3 0.051 0.117 0.436 0.663
C4 0.113 0.045 2.498 0.012
C5 -0.019 0.007 -2.568 0.010
C6 0.009 0.013 0.673 0.501
C7 0.034 0.052 0.657 0.511
C8 -0.124 0.091 -1.364 0.173
R1 -0.382 0.067 -5.693 0.000
R2 -0.652 0.121 -5.405 0.000
R3 -0.236 0.065 -3.604 0.000
U1 -0.194 0.074 -2.615 0.009
U2 -0.195 0.056 -3.477 0.001
U3 -0.139 0.100 -1.397 0.162
U4 0.271 0.094 2.883 0.004
Between Level
O$1 -4.734 0.673 -7.034 0.000
O$2 -2.945 0.668 -4.406 0.000
 Jessica Li posted on Thursday, July 03, 2014 - 11:07 am
========Here is my input=============
TITLE: Org model
DATA: FILE ="\Desktop\g07023.csv";
VARIABLE: NAMES are sid c1 c2 c3 c4 c5 c6 c7 c8 r1 r2 r3 u1 u2 u3 u4 u o;
categorical are o;
Missing are all (9999);
USEVARIABLES are sid c1 c2 c3 c4 c5 c6 c7 c8 r1 r2 r3 u1 u2 u3 u4 o;
WITHIN are c1 c2 c3 c4 c5 c6 c7 c8 r1 r2 r3 u1 u2 u3 u4;
CLUSTER are sid;
Estimator are ml;
o ON c1 c2 c3 c4 c5 c6 c7 c8 r1 r2 r3 u1 u2 u3 u4;
 Jessica Li posted on Thursday, July 03, 2014 - 11:09 am
I should clarify. I was trying to get the predicted value (either categorical or continuous is fine)of the outcome for every case/observation.

 Bengt O. Muthen posted on Thursday, July 03, 2014 - 5:03 pm
If you have a binary DV the intercept is the negative of the threshold. You have an ordinal DV with 3 categories so two thresholds. You can computed the predicted probability for different random intercept values as shown on slide 66 of our Topic 7 handout, where slides 60-66 deal with understanding two-level logistic regression. See handout and video on our website.

We ask that you limit postings to one window.
 ljc posted on Monday, September 29, 2014 - 7:07 am
Slide 66 of topic 7 only has the patterns or cluster sizes. Am I looking in the wrong place?
 Bengt O. Muthen posted on Monday, September 29, 2014 - 10:29 am
Slide 66 refers to the Larsen-Merlo article - this is a good one to study. The slide looks like:

Understanding The Between-Level Intercept
Intra-class correlation
ICC = 0.807/(π2/3+ 0.807) = 0.20
Odds ratios
Larsen & Merlo (2005). Appropriate assessment of neighborhood
effects on individual health: Integrating random and fixed effects in
multilevel logistic regression. American Journal of
Epidemiology, 161, 81-88.
Larsen proposes MOR:
"Consider two persons with the same covariates, chosen randomly from
two different clusters. The MOR is the median odds ratio between the
person of higher propensity and the person of lower propensity."
MOR = exp( √(2* σ2) * Φ-1 (0.75) )
In the current example, ICC = 0.20, MOR = 2.36
Compare β0j= -1 SD and β0j= +1 SD from the mean: For males at the
aggression mean the probability varies from 0.14 to 0.50
 ljc posted on Monday, September 29, 2014 - 11:38 am
Sorry, I hate to be dense, but I don't understand the &# notation.

I think your last sentence has the answer I am looking for which is, the formula for the predicted value for each cluster.
I think I am supposed add (or subtract) the standard deviation to something, but I am not sure what.

Just as a note, I only have a random intercept in my particular example.
 Bengt O. Muthen posted on Monday, September 29, 2014 - 2:00 pm
The text got garbled when copying from the PPT pdf - check the handout instead.
 ljc posted on Monday, September 29, 2014 - 2:54 pm
I found it. It is slide 58 using the version that is on the Mplus homepage.

But it still doesn't help me with probabilities for specific clusters. It just helps me get a range.

I can get cluster specific predictions easily with SAS, but SAS will delete cases with missing x and MPlus won't.

I hope you consider adding predicted values to your to save command in the future. Thanks.
 S.Arunachalam posted on Monday, September 29, 2014 - 9:01 pm
Respected Prof. Muthen I have a similar request:

foe estimator being ML or MLR how to get:
1.) Predicted values (y-hat) and
2.) Residuals (resid)

e.g. I have a latent variable (LV) with three indicators. This LV is a dependent variable Y in the model. So to get the residual of this LV after being predicted by say another independent variable X which also latent with three indicator. i.e.
Y by y1 y2 y3;
X by x1 x2 x3;
Y on X;

Just so, I found an interesting way to get this If X and Y were not latent variables. I can get this from the scatter plot-->save plot data.

However for latent variables this is not there! Please help. (in stata we get this using the predict command for non latent variable regressions)
 Bengt O. Muthen posted on Tuesday, September 30, 2014 - 8:54 am
Answer to ljc:

Perhaps what you are asking for is answered by getting factor scores for the cluster effects, that is, the random intercepts. You get this by Save=FSCORES. Then you plug that into the formula.

Regarding the slide number, I am looking at the 3/29/11 Topic 7 handout at our usual site
 Tihomir Asparouhov posted on Tuesday, September 30, 2014 - 10:00 am
Answer to S.Arunachalam

You can get estimates (posterior mean) for Y and X using

savedata: file is 1.dat; save=FSCORES;

The residuals in the Y on X regression can be computed manually. Just use the estimated coefficient in that regression beta and the estimates for Y and X to get "Y - beta X" residual.
Back to top
Add Your Message Here
Username: Posting Information:
This is a private posting area. Only registered users and moderators may post messages here.
Options: Enable HTML code in message
Automatically activate URLs in message