Hi all,
Would any one be willing to share a nonmem control stream where mixed model
repeated measures (MMRM) is implemented.
Best,
Matts Kagedal
MMRM implementation in nonmem?
Hi Matts,
In my experience, a typical MMRM model is made of many unconnected model parameters usually with an unstructured variance/covariance matrix of residual error and a single inter-individual parameter. It would be relatively painful to copy and paste everything, but the general model could look like this (this was typed directly into email, so it may not work precisely).
Thanks,
Bill
$PRED
USE11 = 0 ; Trial arm 1, time point 1
USE12 = 0 ; Trial arm 1, time point 2
USE21 = 0 ; Trial arm 2, time point 1
USE22 = 0 ; Trial arm 2, time point 2
IF (TIME .EQ. 0 .AND. ARM .EQ. 1) USE11 = 1
IF (TIME .EQ. 1 .AND. ARM .EQ. 1) USE12 = 1
IF (TIME .EQ. 0 .AND. ARM .EQ. 2) USE21 = 1
IF (TIME .EQ. 1 .AND. ARM .EQ. 2) USE22 = 1
EFFECT = USE11 * THETA(1) + USE12 * THETA(2) + USE21 * THETA(3) + USE22 * THETA(4) + ETA(1)
$SIGMA BLOCK(4)
0.1
0.01 0.1
0.01 0.01 0.1
0.01 0.01 0.01 0.1
$THETA
1
1
1
1
$OMEGA
0.1
$ERROR
Y = EFFECT + USE11 * EPS(1) + USE12 * EPS(2) + USE21 * EPS(3) + USE22 * EPS(4)
Quoted reply history
On 4/12/2016 7:10 PM, Matts Kågedal wrote:
> Hi all,
>
> Would any one be willing to share a nonmem control stream where mixed model repeated measures (MMRM) is implemented.
>
> Best,
> Matts Kagedal
Hello,
I don't think both Omega and Sigma can be estimated. We’ve used this code below
for modeling the endpoint which was a change from baseline measure [3 post
baseline measurements and 3 doses]. We tried using either BLOCK in Sigma or
BLOCK in OMEGA. Using a BLOCK with omega gave the same results as SAS. We
shared the ETA for a given time point because we noticed that as time went on
the variability increased.
Thanks,
Mahesh
$PRED
Q4 = 0
Q5 = 0
Q6 = 0
Q7 = 0
Q8 = 0
Q9 = 0
Q10 = 0
Q11 = 0
Q12 = 0
IF (TIME.EQ.1.AND.MG.EQ.0) Q4 = 1
IF (TIME.EQ.1.AND.MG.EQ.5) Q5 = 1
IF (TIME.EQ.1.AND.MG.GT.5) Q6 = 1
IF (TIME.EQ.2.AND.MG.EQ.0) Q7 = 1
IF (TIME.EQ.2.AND.MG.EQ.5) Q8 = 1
IF (TIME.EQ.2.AND.MG.GT.5) Q9 = 1
IF (TIME.EQ.3.AND.MG.EQ.0) Q10 = 1
IF (TIME.EQ.3.AND.MG.EQ.5) Q11 = 1
IF (TIME.EQ.3.AND.MG.GT.5) Q12 = 1
MUX=THETA(1)*Q4 +THETA(2)*Q5 +THETA(3)*Q6 +ETA(1)
IF (TIME.EQ.26) MUX=THETA(4)*Q7 +THETA(5)*Q8 +THETA(6)*Q9 +ETA(2)
IF (TIME.EQ.39) MUX=THETA(7)*Q10 +THETA(8)*Q11 +THETA(9)*Q12+ETA(3)
Y = MUX+EPS(1)
$THETA
1 1 1 2 2 2 3 3 3
$OMEGA BLOCK(3)
2.95E+01
1.80E+01 3.49E+01
1.97E+01 2.84E+01 4.81E+01
$SIGMA 1.00E-07 FIX
$EST MAX=9999 NOABORT PRINT=5 POSTHOC
$COV PRINT=E
Quoted reply history
-----Original Message-----
From: [email protected] [mailto:[email protected]] On
Behalf Of Bill Denney
Sent: Tuesday, April 12, 2016 7:32 PM
To: Matts Kågedal; [email protected]
Subject: Re: [NMusers] MMRM implementation in nonmem?
Hi Matts,
In my experience, a typical MMRM model is made of many unconnected model
parameters usually with an unstructured variance/covariance matrix of residual
error and a single inter-individual parameter. It would be relatively painful
to copy and paste everything, but the general model could look like this (this
was typed directly into email, so it may not work precisely).
Thanks,
Bill
$PRED
USE11 = 0 ; Trial arm 1, time point 1
USE12 = 0 ; Trial arm 1, time point 2
USE21 = 0 ; Trial arm 2, time point 1
USE22 = 0 ; Trial arm 2, time point 2
IF (TIME .EQ. 0 .AND. ARM .EQ. 1) USE11 = 1 IF (TIME .EQ. 1 .AND. ARM .EQ. 1)
USE12 = 1 IF (TIME .EQ. 0 .AND. ARM .EQ. 2) USE21 = 1 IF (TIME .EQ. 1 .AND. ARM
.EQ. 2) USE22 = 1
EFFECT = USE11 * THETA(1) + USE12 * THETA(2) + USE21 * THETA(3) + USE22
* THETA(4) + ETA(1)
$SIGMA BLOCK(4)
0.1
0.01 0.1
0.01 0.01 0.1
0.01 0.01 0.01 0.1
$THETA
1
1
1
1
$OMEGA
0.1
$ERROR
Y = EFFECT + USE11 * EPS(1) + USE12 * EPS(2) + USE21 * EPS(3) + USE22 *
EPS(4)
On 4/12/2016 7:10 PM, Matts Kågedal wrote:
> Hi all,
> Would any one be willing to share a nonmem control stream where mixed
> model repeated measures (MMRM) is implemented.
>
> Best,
> Matts Kagedal
>