RE: PRED for BLQ-like observations

From: [email protected] [mailto:[email protected]] On Behalf Of Nick Holford Sent: Friday, November 20, 2015 12:39 PM To: nmusers Subject: Re: [NMusers] PRED for BLQ-like observations Pavel, Did you test the run time with double the records? I would expect that the MDV=1 records would be largely ignored in the estimation step and not contribute much to run time. Nick On 21-Nov-15 08:59, Pavel Belo wrote: > Thank you Bill, > In my case it exactly doubles the number of records... The records > are daily measures and the code is running slow enough. I'll split the > code into estimation part and one that that is redundant, but uses a > larger file and creates an output. It will be something like > $EST MAXEVALS=9999 SIG=3 NOABORT PRINT=1 SORT CONSTRAIN=5 > METHOD=SAEM NBURN=0 NITER=0 POSTHOC INTERACTION > LAPLACIAN GRD=TG(1-7):TS(8-9) CTYPE=3 CINTERVAL=10 > I guess the best future way is modify something in NONMEM so there is > an option to provide only PRED in the PRED column (version 7.4?). > Thanks! > Pavel > On Fri, Nov 20, 2015 at 01:06 PM, Denney, William S. wrote: > > Hi Pavel, > > The easiest way that I know is to generate your data file with one > set of rows for estimation with M3 and another row just above or > below with MDV=1. NONMEM will then provide PRED and IPRED in the > rows with MDV=1. > > Thanks, > > Bill > > *From:*[email protected] > [mailto:[email protected]] *On Behalf Of *Pavel Belo > *Sent:* Friday, November 20, 2015 11:47 AM > *To:* [email protected]<mailto:[email protected]> > *Subject:* [NMusers] PRED for BLQ-like observations > > Hello The NONMEM Users, > > When we use M3-like approach, the outputs has PRED for non-missing > observations and something else for BLQ (is that PRED=CUMD?). As > in the diagnostic figures PRED for BLQs looks like noise, I remove > them. It is not always perfect, but OK in for most frequent cases. > > When we use count data such as a scale with few possible values > (for example, 0, 1, 2, 3, 4, 5), it makes more sense to use PHI > function (home-made likelihood) for all observations rather than > to treat the count as a continuous variable an apply M3-like > approach to 1 and 5 while only (as we know, they are like LLOQ and > ULOQ). In this case, all PRED values look like noise. A hard way > to replace the noise with PRED value is to simulate PRED for each > point and merge them with the DV and IPRED data. Is there an easy > way? > > (The model runs well and better than when the count is treated as > a continuous variable.) > > Thanks! > > Pavel > -- 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]<mailto:[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. Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin Pharmacol. 2015;79(1):18-27.