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st: Fitting Two-part models for semicontinous data using GLLAMM


From   Anees Abdul Pari <anees.pari@dph.ox.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: Fitting Two-part models for semicontinous data using GLLAMM
Date   Wed, 2 Oct 2013 08:58:58 +0000

Dear all,

Hello there. I have a repeated measures dataset where the primary outcome is a continuous variable (total costs) with substantive proportion of zero values and continuous non-zero (positive) values that are right-skewed. Ideally, I would like to use a two-part model where the outcome variable has a binomial distribution with logit link for the zero versus non-zero part and a gamma distribution with logit link for the non-zero part. As the main outcome is clusterd on individual, I would like to use a GLLAMM model to account for the correlation between measures (random intercept for individuals- as a basic model) whilst adjusting for excessive zeros.

Is there a way where I can use GLLAMM to run this two-part random effect model analysis or is it possible two use TPM command with some kind of adjustment for random effects? I am struggling to come up with a proper code.

I will be eagerly looking forward to your advice and suggestions.


Many thanks

Best wishes

Anees

PS I am a novice to longitudinal modelling
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