Re: A question about handling large-scale data
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
Quoted reply history
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
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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.