Dear Dongyang,
Transforming H+ concentration to the pH scale seems a reasonable idea.
However I would not give much importance to warnings such as "rounding
error" or "termination". You should evaluate your model based on
appropriate changes in objective function value, plausible parameters,
bootstrap confidence intervals of parameters and visual predictive
checks of the model predictions.
If you get errors associated with "numerical difficulty" then try a
different DE solver e.g. ADVAN13 or switch from FOCE to SAEM.
Best wishes,
Nick
On 20/11/2014 6:41 p.m., Liudongyang_hotmail wrote:
Hello All Nonmem Users,
I am modeling intra-gastric H+ concentrations as PD biomarker, which
varies from 10e-7 to 10e-1. I log-transformed original data and used
"Y = LOG(IPRED)+EPS(1)" as log-linear error model firstly. The profile
could be simulated well, but when I fitted data, error messages as
"rounding error ..." or "numerical difficulty ..." showed up. Fitting
was terminated generally. Will anybody share their experiences or tips
on this kind of data?
MANY THANKS IN ADVANCE!
Cheers,
Dongyang Liu, Clinical Pharmacologist
Phase I Unit, Clinical Pharmacology Research Center,
Peking Union Medical College Hospital, Beijing, China
M.P.: +86-18610966092
O.P.: +86-10-69158356
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ +64(21)46 23 53
email: [email protected]
http://holford.fmhs.auckland.ac.nz/
Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A, Pypendop,
B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite pharmacokinetic models
- tests of assumptions and predictions. Journal of Pharmacology & Clinical
Toxicology. 2014;2(2):1023-34.
Ribba B, Holford N, Magni P, Trocóniz I, Gueorguieva I, Girard P, Sarr,C.,
Elishmereni,M., Kloft,C., Friberg,L. A review of mixed-effects models of tumor
growth and effects of anticancer drug treatment for population analysis. CPT:
pharmacometrics & systems pharmacology. 2014;Accepted 15-Mar-2014.
