Conditional on the values of the main effects. I'm working from a reference provided by Dr. Bolker: <br clear="all"><br><div><span class="Apple-style-span" style="border-collapse: collapse; font-family: arial, sans-serif; font-size: 13px; ">Greven, Sonja, and Thomas Kneib. 2010. On the Behaviour of Marginal<br>
and Conditional<br>Akaike Information Criteria in Linear Mixed<br>Models. Biometrika 97, no. 4: 773-789.<br><a href="http://www.bepress.com/jhubiostat/paper202/" target="_blank" style="color: rgb(28, 81, 168); ">http://www.bepress.com/jhubiostat/paper202/</a>.</span></div>
<div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;"><br></span></font></div><div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;">where the marginal likelihood (for a LMM, not a GLMM or other nonlinear mixed model) is as discussed above, y~N(XB,V) (REs have been integrated over) and the conditional likelihood (at its optimum) is evaluated at the MLEs and EB estimates of REs, y | b ~ B*XB + Zb, I*sigma^2) where the b's are the REs.</span></font></div>
<div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;"><br></span></font></div><div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;">So ADMB works with the marginal likelihood, and the optimum value is provided in the .par file. However, it would be nice (at least at this, the exploratory model-selection phase of my work) to also have the conditional likelihood value, which would be obtained (I believe) by plugging the RE estimates and MLEs back into the likelihood function and evaluating. This isn't done automatically by ADMB, but (I think) could be done by changing the .par file to a .pin file, and re-evaluating the model and outputting the first objective function value. I haven't tested this idea yet, though. I'll probably play with it a bit with a GLMM for which I can compare AIC values with other software to try and understand what precisely each is doing.</span></font></div>
<div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;"><br></span></font></div><div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;"><br>
</span></font></div><div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;">Chris</span></font></div><div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;"><br>
</span></font></div><div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;"><br></span></font></div><div><font class="Apple-style-span" face="arial, sans-serif"><span class="Apple-style-span" style="border-collapse: collapse;"><br>
</span></font>-----------------------------<br>Chris Gast<br><a href="mailto:cmgast@gmail.com" target="_blank">cmgast@gmail.com</a><br>
<br><br><div class="gmail_quote">On Tue, Feb 22, 2011 at 9:30 AM, Mark Maunder <span dir="ltr"><<a href="mailto:mmaunder@iattc.org" target="_blank">mmaunder@iattc.org</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
Conditional on what?<br>
<br>
<br>
<br>
Mark Maunder<br>
<br>
Head of the Stock Assessment Program<br>
Inter-American Tropical Tuna Commission<br>
<br>
President<br>
ADMB Foundation<br>
<br>
8604 La Jolla Shores Drive<br>
La Jolla, CA, 92037-1508, USA<br>
<br>
Tel: (858) 546-7027<br>
Fax: (858) 546-7133<br>
<a href="mailto:mmaunder@iattc.org" target="_blank">mmaunder@iattc.org</a><br>
<a href="http://www.fisheriesstockassessment.com/TikiWiki/tiki-index.php?page=Mark+Maunder" target="_blank">http://www.fisheriesstockassessment.com/TikiWiki/tiki-index.php?page=Mark+Maunder</a><br>
<br>
Visit the AD Model Builder project at<br>
<a href="http://admb-project.org/" target="_blank">http://admb-project.org/</a><br>
<br>
See the following website for information on fisheries stock assessment<br>
<a href="http://www.fisheriesstockassessment.com/" target="_blank">http://www.fisheriesstockassessment.com/</a><br>
<div><div></div><div> <br>
<br>
-----Original Message-----<br>
From: <a href="mailto:users-bounces@admb-project.org" target="_blank">users-bounces@admb-project.org</a> [mailto:<a href="mailto:users-bounces@admb-project.org" target="_blank">users-bounces@admb-project.org</a>] On Behalf Of H. Skaug<br>
Sent: Tuesday, February 22, 2011 8:19 AM<br>
To: Chris Gast<br>
Cc: <a href="mailto:users@admb-project.org" target="_blank">users@admb-project.org</a><br>
Subject: Re: [ADMB Users] NLMM Model Selection<br>
<br>
On Tue, Feb 22, 2011 at 5:10 PM, Chris Gast <<a href="mailto:cmgast@gmail.com" target="_blank">cmgast@gmail.com</a>> wrote:<br>
> I'm sorry, I must be getting confused. My message from yesterday (question<br>
> 1) asked if the objective function value in the .par file was the<br>
> post-integration marginal likelihood, to which you responded in the<br>
> negative, but now it seems as if you're saying what I had originally<br>
> postulated is true. Maybe it's just a terminology difference. It is my<br>
> understanding that the .par file contains the optimum loglikelihood value<br>
> obtained, where the loglikelihood value is marginalized over the random<br>
> effects. Perhaps there is some miscommunication? I think we're talking<br>
> about the same thing.<br>
<br>
Yes, we are. I misunderstood your original question.<br>
<br>
> Since the marginal likelihood is available in the .par file, is there a way<br>
> to output the conditional likelihood following optimization?<br>
<br>
No, not any direct way that I am aware of. It is possible that this<br>
is what you get before the random effects kick in (assuming those<br>
active in phase 2 or later).<br>
<br>
hans<br>
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