Truncated normal distribution for continuous covariate with known mean and standard error
Dear NMUsers,
I would like to implement a truncated normal distribution for weight for
use in a simulation, with a pre-specified mean and standard deviation.
What works so far is this (w.o. truncation, which I found in the NONMEM
user guides):
$PK
IF (ICALL.EQ.4.AND.NEWIND.NE.2) THEN
CALL RANDOM(5,R)
ENDIF
IF (ICALL.EQ.4) WT=70+10*R; mean of 70 with SD 10
$SIM (12345) (...) (...) (...) (54676 NORMAL); I have a total of five
random number generators i.e. 4 different covariates, which I want to
simulate distributions for.
Adding a DOWHILE loop does not seem to work (either I get error messages
or NONMEM stagnates after performing the sims and never finishes) - I think
it's a coding issue on my part, in regard to the IF THEN ELSE statements
and DOWHILE statement:
IF (ICALL.EQ.4.AND.NEWIND.NE.2) THEN
CALL RANDOM(5,R)
ENDIF
IF (ICALL.EQ.4) WT=70+10*R;
DOWHILE (WT.GT.50.OR.WT.LT.100); truncation limits of 50 and 100
ENDDO
Other ways to generate a normal truncated distribution can be coded as
(from Metrum Institute course 210):
$PK
IF (ICALL.EQ.4) THEN
WT=THETA(1) + ETA(1)
DOWHILE (WT.LT.20.OR.WT.GT.100)
CALL SIMETA(ETA)
WT=THETA(1) + ETA(1)
ENDDO
ENDIF
$SIM (2345 NEW)
Yet, I am unsure of how to incorporate my known mean and standard deviation
using this approach.
Hope you can help. Thanks in advance.
Best regards,
Yassine