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Re: [NMusers] Mixture model with logistic regression

From: Gerry Sheng <shengyc_at_gmail.com>
Date: Sat, 20 Feb 2016 22:25:43 +0000

Hi Mark,

My first suggestion is you can start from simpler mixture model (e.g. 2
distributions) and only focus on those have AEs. 68% patients without AE is
a big disturbance to intercept. Only negative infinity of intercept in
logistic model can give a probability=0. Secondly, you can try to use SAE=
M
method with mu reference. Based on my own experience, FOCE method is not as
powerful as SAEM in likelihood estimations. Good luck.

BW,
Yucheng Sheng

UCL School of Pharmacy
29-39 Brunswick Square
London WC1N 1AX
Email. shengyc_at_gmail.com

On 19 February 2016 at 22:30, Mark Sale <msale_at_nuventra.com> 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 thi=
s
> 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, the=
re
> 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 h=
oc
> 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, sti=
ll
> 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 distributio=
n
> (and OMEGA), and it still gave me a very small difference in the intercep=
t
> 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
>
> msale_at_nuventra.com <http://msale@kinetigen.com>
>
> www.nuventra.com
>
>
>
>

Received on Sat Feb 20 2016 - 17:25:43 EST

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