Zero-inflated Poisson regression in m... PreviousNext
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 Yu Ye posted on Friday, February 25, 2005 - 2:55 pm
I am wondering if Zero-inflated Poisson regression can be modelled in multilevel structure. I can't find the example in Mplus manual (Chapter 9, version 3). I am working on a project to predict the number of prior emergency room visits in which patients are nested in ERs.
In particular I would like to know if two random intercept and two slopes would be modelled for both the counts and probability as in the normal ZIF regression.

Thanks a lot in advance.

Yu
 Linda K. Muthen posted on Saturday, February 26, 2005 - 4:05 pm
No, this is not available in the current version of Mplus. Only continuous and categorical outcomes can be modeled with multilevel models. If you look up ESTIMATOR in the Mplus User's Guide, you will find a summary of which types of analyses are available for different outcome types and which estimators are available for these combinations. You may find this tabel useful.
 Linda Stanley posted on Tuesday, December 12, 2006 - 2:16 pm
I am trying to do a similar analysis as Yu Ye describes in the beginning of this thread where a zero-inflated Poisson regression or zero-inflated negative binomial multilevel model seems appropriate. In my case, the dependent variable is a measure of drug use, and thus, it seems very similar to the two-part modeling being done in MPlus with longitudinal data since there are many zeros. However, my data is nested, cross-sectional. Can MPlus do this type of analysis?

Thank you!
Linda S.
 Bengt O. Muthen posted on Tuesday, December 12, 2006 - 2:46 pm
Yes, 2-level ZIP regression can be done in Mplus using ML. Both the intercept and the slopes can be random. 2-level, two-part regression modeling is also available.
 Leslie Rutkowski posted on Friday, March 01, 2013 - 2:17 pm
Hi Linda and Bengt,

I'm trying to fit a multilevel ZIP model with a random intercept. Everything seems sensible with the exception of no intercept variance estimate. I'm not sure what I've missed in the syntax.

A simplified specification, starting with the variable statement, follows.

Thanks for your suggestions.
Leslie

VARIABLE:
NAMES ARE some variables;
USEVARIABLES ARE some variables ;
COUNT IS bully (i);
MISSING IS .;
WITHIN with in variables;
BETWEEN btwn vars ;
CLUSTER schlid;
BWEIGHT = schwgt;
BWTSCALE = sample;
WEIGHT = stuwgt;
WTSCALE = cluster;
STRATIFICATION = idstrate;
SUBPOPULATION = (IDCNTRY EQ 51);
ANALYSIS: TYPE = TWOLEVEL COMPLEX;
MODEL:
%WITHIN%
bully ON ssupp1 pv1 age male slfest ageimm lang tearel1 s_pinv1 satch ses chimm fgnbor;
bully#1 ON;
%BETWEEN%
bully on schsize supp urban dispol1 atch pinv mssupp1 mpv1 mage mmale mslfest mlang mses mtearel1 ms_pinv1 msatch ;
bully#1 ON;
 Linda K. Muthen posted on Friday, March 01, 2013 - 6:07 pm
Add

bully;

to the between part of the MODEL command.
 Leslie Rutkowski posted on Monday, March 04, 2013 - 8:14 am
Hi Linda,

Thanks for your response. Adding this variable to the between part results in the following:

*** ERROR
One or more between-level variables have variation within a cluster for
one or more clusters. Check your data and format statement.

Between Cluster ID with variation in this variable
Variable (only one cluster ID will be listed)

This seems to make intuitive sense since the variable really does have within cluster variation given its role as a within-group variable.

Thanks for further insights.
Leslie
 Linda K. Muthen posted on Monday, March 04, 2013 - 8:22 am
Don't put bully on the BETWEEN list. Add it to the between part of the MODEL command:

%BETWEEN%
bully on schsize supp urban dispol1 atch pinv mssupp1 mpv1 mage mmale mslfest mlang mses mtearel1 ms_pinv1 msatch ;
bully#1 ON;
bully;
 Leslie Rutkowski posted on Monday, March 04, 2013 - 2:47 pm
Thanks - that's clear.
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