Dear Hans,<br><br>Many thanks for the response. I have about 40,000 mothers and about 150,000 children. For each child, we know whether s/he has survived to age 10 and, if not, age at death. Now I want to estimate a joint model with three random intercept logistic regression on (1) if a child died at infancy (age at death <1), (2) if a child died in age 1-5, and (3) if a child died in age 6-10. It is easy to estimate these models separately, assuming Gaussian, non-Gaussian, or a non-parametric heterogeneity at mother-level. The difficulty arises when I try to estimate these equations jointly. For multivariate Gaussian heterogeneity, there is aML and Sabre (in theory GLLAMM can also do it but it is too slow to be practical); but none of them handles multivariate non-Gaussian heterogeneity. ADMB seems to be the only hope at this moment (besides programming the whole thing in Fortran).<br>
<br>In this particular case, the joint model is important because the correlations between the heterogeneity terms are of substantive interest. <br><br>Best,<br>Shige<br><br><div class="gmail_quote">On Mon, Jun 1, 2009 at 11:10 PM, H. Skaug <span dir="ltr"><<a href="mailto:hskaug@gmail.com">hskaug@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">Shige,<br>
<br>
multivariate log-normal for the unobserved hetegeineity is OK, but you<br>
need to give us a brief summary of your model, including the number of<br>
"individuals", if you want more detailed feedback<br>
<br>
The largest collection of latent variable models in ADMB is found here:<br>
<br>
<a href="http://www.otter-rsch.com/admbre/examples.html" target="_blank">http://www.otter-rsch.com/admbre/examples.html</a><br>
<br>
Hans<br>
<div><div></div><div class="h5"><br>
<br>
On Sun, May 31, 2009 at 12:50 AM, Shige Song <<a href="mailto:shigesong@gmail.com">shigesong@gmail.com</a>> wrote:<br>
> Dear All,<br>
><br>
> I am trying to port an analysis from aML to ADMB. This is a multilevel<br>
> multiprocess model (some people call it multivariate multilevel model) of<br>
> child mortality. I am jointly modeling infant mortality (death before age<br>
> one), mortality between age 1-10, and mortality between age 11-20. Because<br>
> aML assumes a multivariate normal distribution for the unobserved<br>
> heterogeneity terms, some reviwers think my results are minly driven by this<br>
> distributional assumption. I would like to try alternative distribution<br>
> assumption for these unobserved hetegeineity terms such as multivariate<br>
> log-normal or multivariate t. ADMB seems to be the only softare choice for<br>
> this.<br>
><br>
> It will be really great if there is an example of multilevel multiprocess<br>
> model using ADMB so that I can tailor it to suite my own research needs. Can<br>
> anybody help me with this?<br>
><br>
> Many thanks.<br>
><br>
> Best,<br>
> Shige<br>
><br>
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</blockquote></div><br>