Hi Johan,
If you could share your code and a relevant snippet of your dataset you
might get more specific help. Without such detail: Bill's suggestion
(time-varying covariate) could extend to the covariance step as well -
those calculations might be more sensitive to the different values
generated (values may be much smaller or larger because they depend on
individual eta's). If you use differential equations, the additional
time steps requested by EVID=2 might be more sensitive in a similar way.
BTW, with nm7.3 onwards there is a system to prevent EVID=2 calculations
in the est/cov steps, by using MDV=101 or larger. In intro nm7 guide I66:
"I.66 Ignoring Non-Impact Records During Estimation (NM73)
Typically users may produce data files that are augmented with
additional non-dose, non-
observation records in order to output predicted values at additional
times to create high
resolution curves. However, too many of such records tend to slow down
the estimation
analysis. As of NM73, if an MDV is set to a value greater than or equal
to 100, it is converted to
that value minus 100 upon input, but will not be used during estimation
or covariance
assessment, only for table outputting. This option allows you to use the
same file for estimation
and table outputs, without significantly slowing down the estimation. So
if MDV=101, it will be
converted to 1 upon use for final evaluations, and the records will be
ignored during estimation."
Hope this helps & best regards,
Jeroen
http://pd-value.com
jer...@pd-value.com
@PD_value
+31 6 23118438
-- More value out of your data!
On 23/4/19 5:33 pm, Johan Rosenborg wrote:
Hello everybody,
In order to obtain predicted values in a PopPK analysis without
covariates at points in time with no actual values I have inserted
extra rows indicated with EVID=2. The covariance step is completed
when including these extra rows and precision of the parameter
estimates are adequate. When omitting the extra rows
{IGNORE=(EVID.EQ.2)}, I get exactly the same parameter estimates, the
covariace step can be completed with some difficulty, but precision of
the parameter estimates are now inadequate. I use METHOD=1 and just
like Ahmed Abbas Suleiman experienced
(https://cognigencorp.com/nonmem/current/2013-February/4440.html 2
<https://cognigencorp.com/nonmem/current/2013-February/4440.html>), my
outcome did not differ between the two conditions when setting
METHOD=0. I saw that William Denney has responded to a similar
question in 2016
(https://cognigencorp.com/nonmem/current/2016-February/6085.html 2
<https://cognigencorp.com/nonmem/current/2016-February/6085.html>).
I cannot see any response to Ahmed’s comment; do you Bill or somebody
else have any idea why the outcomes differ with METHOD=1 but not with
METHOD=0 in NonMem when including extra rows in the data set?
Thank you in advance and kind regards,
Johan
