RE: [NMusers] NONMEM6: BQL and YLO

Dear Pavel and NONMEM6 users,
 
I believe the example referred to implements Stuart Beal's strategy II
(J. Pharmacokin. Pharmacodyn. 32:213-243,2005) described specifically on
page 230-231 of that article as well as in a previous article (J.
Pharmacokin. Pharmacodyn. 28:481-504, 2001). That approach involves
deletion of the DV<LOQ from the calculation of the likelihood (MDV=1)
and corrects the likelihood for all remaining observations in the data
set. Examine the PR_Y values for observations that are above but near
the LOQ. This is at least a somewhat better estimate of the likelihood
for the data remaining in the data set. For the users information,
Stuart allows the calculation of the probabilities associated with
DV<LOQ, MDV=1 if measured values are availble but, as you note, these do
not influence -2LL. In most data sets, DV<LOQ values are not reported
quantitatively.
 
Hope this is helpful.
 
Tom

________________________________

From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com]
On Behalf Of nonmem_at_optonline.net
Sent: Friday, January 05, 2007 9:12 PM
To: nmusers_at_globomaxnm.com
Subject: [NMusers] NONMEM6: BQL and YLO



Hello NONMEM6 users,

At one conference new features of NONMEM6 were presented. It was stated
that NONMEM6 takes care of BQL values and improves likelihood. I tried
to find information in the manuals and found the YLO example and the
following statement: "Last observation record (below) has DV < LOQ (LOQ
= 1) and MDV = 1. This observation does not contribute to the -2LL
estimate. However, probability that DV is > LOQ can be tabled using
PRB=PR_Y." Therefore (?), taking care of BQLs in the YLO examlpe does
not improve the results.

1. Is there a way to utilize BQLs and improve likelihood?

2. How helpful is the estimate of PR_Y?

Thank you!

Pavel




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Received on Mon Jan 08 2007 - 09:29:45 EST