RE: 95% prediction interval and $OMEGA
Hello Kelong,
Did you try to put TRUE=FINAL in the $simulation record.
I suggest also to input you parameters using MSFI
Bests,
Samer
Quoted reply history
-----Original Message-----
From: [EMAIL PROTECTED] on behalf of Han, Kelong
Sent: Thu 6/5/2008 21:49
To: [email protected]
Subject: [NMusers] 95% prediction interval and $OMEGA
Dear NONMEM users,
I am trying to calculate and plot the 95% prediction interval (PI) for a
single-subject multiple-dosing PO dataset by simulating 1000 DV values.
It seems that bigger initial estimate of omega ($OMEGA) leads to wider 95%
prediction band. I understand that OMEGA directs the variability in
"ERR(1)" in single-subject data, but I am still confused.
Could anyone help me pick up a $OMEGA to calculate 95% PI, or solve this
problem in another way? Thanks!
Below is the control stream (the best-fit THETA values were used as
initials):
--------------------------------------------------
$DATA po.csv IGNORE=C
$INPUT ID TIME CONC=DV AMT MDV CMT
$SUBROUTINE ADVAN2 TRANS2
$PK
CL = THETA(1)
V = THETA(2)
KA = THETA(3)
S2 = V
F1 = 1
$ERROR
IPRED=F
Y=F+ERR(1)
$THETA (0.398)
$THETA (64.3)
$THETA (0.425)
$OMEGA 1.2
$SIMULATION (324422) SUBPROBLEMS=1000
$ESTIMATION METHOD=0 NOABORT MAXEVAL=9999 PRINT=0
$COVARIANCE
$TABLE TIME DV IPRED NOPRINT NOHEADER FILE=
---------------------------------------------------------
Any input would be greatly appreciated.
Thanks!
Sincerely
--
Kelong Han
PhD student