mittal.
From: Jeroen Elassaiss-Schaap (PD-value B.V.)
Sent: Saturday, February 20, 2016 4:35 PM
To: Mark Sale
Cc: nmusers@globomaxnm.com
Subject: Re: [NMusers] Mixture model with logistic regression
Hi Mark,
Is it indeed a logistical model or is it an ordered categorical? I assu
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
*Sent:* Saturday, February 20, 2016 2:44 PM
*To:* Mark Sale
*Cc:* nmusers@globomaxnm.com
*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
Cc: nmusers@globomaxnm.com
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
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
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
ox 591
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-Original Message-
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On
Behalf Of Paul Hutson
Sent: 07 May 2013 17:32
To: nmusers@globomaxnm.com
Subject: [NMusers] Mixture model simulation
Dear Users:
I n
ht be different for the
subgroups?
Erik
From: owner-nmus...@globomaxnm.com [owner-nmus...@globomaxnm.com] on behalf of
Paul Hutson [prhut...@pharmacy.wisc.edu]
Sent: Tuesday, May 07, 2013 5:31 PM
To: nmusers@globomaxnm.com
Subject: [NMusers] Mixture
aul Hutson
Sent: 07 May 2013 17:32
To: nmusers@globomaxnm.com
Subject: [NMusers] Mixture model simulation
Dear Users:
I note the Jan 26, 2013 response to Nick Holford's query about results from
the use of the $MIX mixture model for simulation. I have created a data set
of N=100 subjects usin
Well, it was the wrong guess, MIXNUM should work
--
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web:www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel:(301) 767 5566
should it be IF(MIXEST.EQ.2) Z=0 for the fitting run?
On 5/7/2013 1
should it be IF(MIXEST.EQ.2) Z=0 for the fitting run?
--
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web:www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel:(301) 767 5566
On 5/7/2013 11:31 AM, Paul Hutson wrote:
Dear Users:
I note t
Dear Users:
I note the Jan 26, 2013 response to Nick Holford's query about results
from the use of the $MIX mixture model for simulation. I have created a
data set of N=100 subjects using R to randomly distribute their
covariates, both continuous and categorical. I then ran the following
sim
sage-
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On
Behalf Of Nick Holford
Sent: Friday, January 25, 2013 4:00 PM
To: nmusers
Subject: Re: [NMusers] Mixture model simulation
Tom (and others),
Thanks for your replies and suggestions. I've looked at the behaviour
[n.holf...@auckland.ac.nz]
Sent: Friday, January 25, 2013 10:00 PM
To: nmusers
Subject: Re: [NMusers] Mixture model simulation
Tom (and others),
Thanks for your replies and suggestions. I've looked at the behaviour of
both MIXNUM and MIXEST.
As Tom stated it seems that MIXNUM describe
I am
not certain what value MIXEST will have for each individual.
Best wishes,
Tom Ludden
-Original Message-
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On
Behalf Of Nick Holford
Sent: Friday, January 25, 2013 2:51 AM
To: nmusers
Subject: [NMusers] Mixture
...@globomaxnm.com] Per
conto di Nick Holford
Inviato: venerdì 25 gennaio 2013 09:51
A: nmusers
Oggetto: [NMusers] Mixture model simulation
Hi,
I've been puzzled by the behaviour of NONMEM when trying to simulate with a
mixture model.
The data file has 1000 subjects. I simulate 100 times (see control s
, 2013 9:50 AM
To: nmusers
Subject: [NMusers] Mixture model simulation
Hi,
I've been puzzled by the behaviour of NONMEM when trying to simulate
with a mixture model.
The data file has 1000 subjects. I simulate 100 times (see control
stream below).
The overall number of subjects with MIXEST of 1
Hi,
I've been puzzled by the behaviour of NONMEM when trying to simulate
with a mixture model.
The data file has 1000 subjects. I simulate 100 times (see control
stream below).
The overall number of subjects with MIXEST of 1 is 45%. There are no
simulated values of 99. All values are either 1
ryland.edu<mailto:ctm-unsubscr...@lists.umaryland.edu>
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On
Behalf Of Fisher Dennis
Sent: Thursday, July 12, 2012 4:25 PM
To: nmusers@globomaxnm.com
Subject: [NMusers] Mixture model
Colleagues
I am analyzing data in w
Colleagues
I am analyzing data in which there are two distinct populations as a result of
CYP2D6 deficiency. In one dataset, there are 18 subjects with rich data; one
of these subjects is markedly different. In that the incidence of 2D6
deficiency is reported to be < 10%, one would expect onl
Gaurav,
Some suggestions:
1. I cannot see how you are introducing treatment into the model. You
have something that is a function of time (EFF1) but not of treatment.
I'd suggest including whether treatment is being used or not
(statistical/regulatory view from a dark cave) or a function of d
Dear All,
I am trying to model a tumor size data at different time points using
NONMEM. There is high variability in baseline tumor size and their might
be sub-populations in the dataset with different distribution for size
progression. For example, in many cases the baseline tumor size is aroun
.2) Q2=1 ; PDT IS 2 FOR BIOMARKER
>
>
>
> Y=Q1*Y1+Q2*Y2
>
>
>
> $MIX
>
> NSPOP=2
>
> P(1)=THETA(11) ;PATHOLOGIC
>
> P(2)=1-THETA(11) ;NON-PATHOLOGIC
>
>
>
> $THETA
>
> ...
>
> (0,FIX) ;THETA(8) FIXED TO ZERO FOR NON PROGRESSERS
>
&
R NON PROGRESSERS
...
$OMEGA
1 FIX
1 FIX
$SIGMA
1 FIX
1 FIX
From: owner-nmus...@globomaxnm.com on behalf of Nick Holford
Sent: Sun 1/16/2011 1:49 AM
To: nmusers@globomaxnm.com
Subject: Re: [NMusers] Mixture model for Disease Progression
Mahesh
Mahesh,
Do you have a good biological reason to divide your population into
different subpopulations?
If not then a more flexible way to describe an association between
baseline and slope is estimate the covariance between the random
effects. This does carry with it the explicit assumption t
Hello,
I am trying some simple linear disease progression analysis and the data
suggests that there are 2 populations in the dataset (Low Baseline, Low
Slope vs. High Baseline, High Slope). It appears that that population
consists of progressers and non-progressers (The Pharmacometrics
textbook de
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