Re: NONMEM vs SPSS
Gavin,
NONMEM has been noted (Senn et al 2012) to produce smaller SE (R-1 S R-1 method) compared to estimates from Mathcad, SAS, GenStat and R. The Mathcad estimates were identical to SAS, Genstat and R when using numerical derivatives and larger when based on the expected Fisher information matrix. So there is clearly some kind of between and within program standard error describing the uncertainty in standard error estimates obtained from different methods.
Comparisons of NONMEM asymptotic SE to those estimated by non-parametric bootstraps have shown they are often similar for relatively 'linear' (in the mathematical not PK sense) models but are different (usually smaller) as the model becomes more 'non-linear'. The 95% confidence intervals also tend to become asymmetrical which invalidates the use of an asymptotic SE for calculation of confidence intervals.
I prefer to use bootstrap derived confidence intervals to describe uncertainty of parameter estimates. The use of the SE is the standard error of traditional approaches.
Best wishes,
Nick
Senn, S., et al. (2012). "The ghosts of departed quantities: approaches to dealing with observations below the limit of quantitation." Stat Med 31(30): 4280-4295.
Quoted reply history
On 30/03/2014 5:55 a.m., Gavin Jarvis wrote:
> Dear NONMEM Users
>
> Does anyone have a view on the relative merits/reliability/accuracy of NONMEM ($COV step) vs SPSS (NLR) with respect to their derived values of the parameter standard errors and parameter correlation matrices?
>
> The data I am analysing are single subject (not population). Parameter estimates from the two programs are, to all intents and purposes, identical. However, the SE values from NONMEM $COV are consistently smaller by 1.5-2.0-fold.
>
> Any thoughts?
>
> Gavin
>
> __________________________________________________
>
> *Dr Gavin E Jarvis MA PhD VetMB MRCVS*
>
> University Lecturer in Veterinary Anatomy
>
> Department of Physiology, Development & Neuroscience
>
> Physiological Laboratory
>
> Downing Street
>
> Cambridge
>
> CB2 3EG
>
> Tel: +44 (0) 1223 333745
>
> Fellow and College Lecturer in Pharmacology
>
> Selwyn College
>
> Cambridge
>
> CB3 9DQ
>
> Tel: +44 (0) 1223 761303
>
> Email: [email protected] <mailto:[email protected]>
>
> Web: www.pdn.cam.ac.uk/staff/jarvis < http://www.pdn.cam.ac.uk/staff/jarvis >
>
> Twit: @GavinEJarvis
--
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/
McCune JS, Bemer MJ, Barrett JS, Scott Baker K, Gamis AS and Holford NH (2014)
Busulfan in infant to adult hematopoietic cell transplant recipients: a
population pharmacokinetic model for initial and bayesian dose personalization.
Clin Cancer Res 20:754-763.
Størset E, Holford N, Hennig S, Bergmann TK, Bergan S, Bremer S, Åsberg A,
Midtvedt K and Staatz CE (2014) Improved prediction of tacrolimus
concentrations early after kidney transplantation using theory-based
pharmacokinetic modelling. Br J Clin Pharmacol Accepted online 20 Feb 2014
DOI:10.1111/bcp.12361