Re: 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.
Quoted reply history
On Fri, Feb 19, 2016 at 2:30 PM, Mark Sale <[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
>
> [email protected] http://[email protected]
>
> www.nuventra.com
>
>
>
>