Hi Mark,
Is it indeed a logistical model or is it an ordered categorical? I
assume you refer to the latter. Not sure how you get your second
category otherwise.
Anyway, to me it reads like you are trying to have the mixture model
describe exactly what the omega is trying to describe. Perhaps you could
drop the omega all together? (or fix to a small value)
I also like Bob's suggestion, I would go for it ($NPAR!).
Hope this helps,
Jeroen
http://pd-value.com
[email protected]
@PD_value
+31 6 23118438
-- More value out of your data!
Op 20-02-16 om 21:01 schreef Mark Sale:
Matts,
Thanks for your insights. But, the issue isn't the post hoc
values. With the mixture model the OMEGA on the intercept is huge
(680), and the entire population is in the low intercept value group
(Intercept = -11). Then to accommodate the patients with frequent
AEs, it assigns a (post hoc) ETA of +15, giving an individual value
for intercept of 6 (and a probability of the AE of ~1, as it should.
My question is whey does it refuse to simply put those 8% of the
patients in a sub population with intercept = 6, ETA=0. rather than
saying the expected value is -11, with ETA = +15. Even when I fix the
fractions in the subpopulations for the observed values, and fix OMEGA
to a small, reasonable value, and fix the intercept values for the 3
populations to reasonable values it will still do this. The only
thing that has worked is to assign each subject to the apparent
population in the data set.
Mark
Mark Sale M.D.
Vice President, Modeling and Simulation
Nuventra, Inc. ™
2525 Meridian Parkway, Suite 280
Research Triangle Park, NC 27713
Office (919)-973-0383
[email protected] <[email protected]>
www.nuventra.com <http://www.nuventra.com>
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*From:* Matts Kågedal <[email protected]>
*Sent:* Saturday, February 20, 2016 2:44 PM
*To:* Mark Sale
*Cc:* [email protected]
*Subject:* Re: [NMusers] Mixture model with logistic regression
Hi Mark,
The pattern you see in the posthocs could possibly be a shrinkage
phenomenon. I.e. patients with AE most of the time will have the same
ETA, while patients with no AE will have the same ETA and there will
be a third group in between. If shrinkage is causing this, you should
not expect any improvement with a mixture model. Before you reject
your original model I would therefore also evaluate it by simulation
and re-estimation. I think it is quite possible that you will retreive
a similar pattern in the posthocs even when you simulate based on a
normal distribution.
Best,
Matts Kågedal
Pharmacometrics, Genentech.
On Fri, Feb 19, 2016 at 2:30 PM, Mark Sale <[email protected]
<mailto:[email protected]>> wrote:
Has anyone every tried to use a mixture model with logistic
regression? I have data on a AE in several hundred patients,
measured multiple times (10-20 times per patient). Examining the
data it is clear that, independent of drug concentration, there is
very wide distribution of this AE, 68% of the patients never have
the AE, 25% have it about 20% of the time and the rest have it
pretty much continuously, regardless of drug concentration. (in
ordinary logistic regression, just glm in R, there is also a nice
concentration effect on the AE in addition). Running the usual
logistic model, not surprisingly, I get a really big ETA on the
intercept, with 68% of the people having ETA small negative, 25%
ETA ~ 1 and 7% ETA ~ 10. No covariates seem particularly
predictive of the post hoc ETA. I thought I could use a mixture
model, with 3 modes, but it refused to do that, giving me
essentially 0% in the 2nd and 3rd distribution, still with the
really large OMEGA for the intercept. Even when I FIX the OMEGA
to a reasonable number, I still get essentially no one in the 2nd
and 3rd distribution. I tried fixing the fraction in the 2nd and
3rd distribution (and OMEGA), and it still gave me a very small
difference in the intercept for the 2nd and 3rd populations.
Is there an issue with using mixture models with logistic
regression? I'm just using FOCE, Laplacian, without interaction,
and LIKE.
Any ideas?
Mark
Mark Sale M.D.
Vice President, Modeling and Simulation
Nuventra, Inc. ™
2525 Meridian Parkway, Suite 280
Research Triangle Park, NC 27713
Office (919)-973-0383 <tel:%28919%29-973-0383>
[email protected] <http://[email protected]>
www.nuventra.com <http://www.nuventra.com>
