Dear Alison,
It may be clearer. It certainly would capture most covariate changes but on the other hand you may need to used EVID=2 even when the physiological variable change is at an observation/dose event (if you want to have the covariate values feed forward rather than backwards). Also, you may not need to have to use EVID=2 to make the covariate change at other times than event times (as my example code tried to illustrate). Best regards, Mats Mats Karlsson, PhD Professor of Pharmacometrics Dept of Pharmaceutical Biosciences Faculty of Pharmacy Uppsala University Box 591 75124 Uppsala Phone: +46 18 4714105 Fax + 46 18 4714003 <http://www.farmbio.uu.se/research/researchgroups/pharmacometrics/> www.farmbio.uu.se/research/researchgroups/pharmacometrics/ From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On Behalf Of Alison Boeckmann Sent: 27 August 2013 22:46 To: siwei Dai; ajbf Cc: nmusers@globomaxnm.com Subject: Re: [NMusers] Time-varing covariate There have been a number of interesting comments. The original issue has to do with the way this is described in on-line help for EVID. Would it be more clear if this said: a physiological variable changes (and this is at a different time than any observation or dose event). Or can someone suggest a better wording that would not add to the confusion? On Fri, Aug 23, 2013, at 10:51 AM, siwei Dai wrote: Hi, Nick: Thank you for the response. I meant to say EVID = 2 but not '4', my mistake. In the user guide, it says: 2 Other-type event. The DV data item is ignored. Dose-related data items must be zero. Examples of other-type events are: A compartment is turned on or off (CMT specifies which compartment is to be turned on or off); a prediction is obtained at a speci- fied time so that it may be displayed in a table or scatterplot (PCMT specifies the compartment from which the prediction is obtained); a physiological variable changes. I am asking the question because I thought that usually the covariates stay the same, but I want to add a covariate that changes during the day, so every observation line will have a different covariate value. If I understand your email correctly, I don't need to do anything special to treat this type covariates then? Thanks! Best regards, Siwei On Fri, Aug 23, 2013 at 1:10 PM, Nick Holford <n.holf...@auckland.ac.nz> wrote: Siwei, I don't know why you think this complicated. Suppose you have age (AGE) as a covariate. This must of course be a time varying covariate if it is intended to be the current age. And you might have weight (WT) or creatinine clearance (CLCR) as covariates which typically change with time. So just code the $INPUT data items and use them as you wish e.g. $INPUT ID TIME AGE WT CLCR etc ... $PK ; CL=(CLnon-renal*f(age) + CLrenal*f(renal_function)) * allometric WT CL=(THETA(1)*EXP(THETA(2)*(AGE-40)) + THETA(3)*CLCR/100)*(WT/70)**0.75 EVID=4 has nothing to do with using time varying covariates. Perhaps you could explain more clearly what your problem is and why you think it is complicated to use time varying covariates? Best wishes, Nick On 23/08/2013 6:00 p.m., siwei Dai wrote: Hi, Dear NMusers: I want to add a time-varing covariate in my model. For example, blood pressure or blood flow as covariates. But I am not sure how to do it. I see some earlier threads to discuss it but they all use complicated methods. I am wondering if there are any new way to do it in NM 7.2? I see in the user guide that EVID=4 can indicate physiological change. Is this what I should use? Thank you very much for any suggestions. Best regards, Siwei -- 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 <tel:%2B64%289%29923-6730> mobile:NZ +64(21)46 23 53 <tel:%2B64%2821%2946%2023%2053> FR +33(7)85 36 84 99 <tel:%2B33%287%2985%2036%2084%2099> email: n.holf...@auckland.ac.nz http://holford.fmhs.auckland.ac.nz/ Holford NHG. Disease progression and neuroscience. Journal of Pharmacokinetics and Pharmacodynamics. 2013;40:369-76 http://link.springer.com/article/10.1007/s10928-013-9316-2 Holford N, Heo Y-A, Anderson B. A pharmacokinetic standard for babies and adults. J Pharm Sci. 2013: http://onlinelibrary.wiley.com/doi/10.1002/jps.23574/abstract Holford N. A time to event tutorial for pharmacometricians. CPT:PSP. 2013;2: http://www.nature.com/psp/journal/v2/n5/full/psp201318a.html Holford NHG. Clinical pharmacology = disease progression + drug action. British Journal of Clinical Pharmacology. 2013: http://onlinelibrary.wiley.com/doi/10.1111/bcp.12170/abstract -- Alison Boeckmann alisonboeckm...@fastmail.fm
