Re: T matrix

From:Nick Holford Subject:Re: [NMusers] T matrix Date:Sat, March 9, 2002 4:09 pm Leonid, Thanks for these helpful comments. Leonid Gibiansky wrote: > In my experience, SEs provided by NONMEM worth a lot. We compared them with > the bootstrap or log likelihood profile SEs and found out that Is this work published yet? In Jul 2000 you said you were planning to publish. http://www.boomer.org/pkin/PK00/PK2000103.html I would be keen on seeing the details of your results. > in most > cases the results are similar with the exception of the parameters with > intrinsically non-symmetric distribution (e.g., bounded by zero, defined > with large error and with the estimate close to zero). It is exactly these parameters with an asymmetric estimation confidence that are the main reason I am personally interested in obtaining a confidence interval e.g. if I estimate Emax as part of a model to test if a drug is effective or not then I want to know how reliable the Emax value is. Typically Emax will be bounded by zero and defined with large error and may well have an estimate close to zero for many drugs in early drug development. > Moreover, log > likelihood profile SEs with FO are less reliable (too narrow) compared to > NONMEM estimates. Bootstrap is reasonable, but with fitting of 1000 or so > problems you cannot be sure that your tails of the bootstrap distributions > are not the local minimums (not to mention extra time and efforts that you > need to invest in bootstrap). Summarizing, we found that NONMEM SEs provide > quick and in most cases reliable information which is rarely corrected by > more computer-intensive techniques. I accept your point that FO may be misleading unless one has taken the time to establish the log-likelihood difference required to define the desired confidence interval e.g. Assessment of Actual Significance Levels for Covariate Effects in NONMEM Whlby U.; Jonsson E.N.; Karlsson M.O. Journal of Pharmacokinetics and Pharmacodynamics, June 2001, vol. 28, no. 3, pp. 231-252(22). Note that I would not use the log-likelihood profile to estimate the parameter SE (which IMHO is of no intrinsic merit) but would use it to define a confidence interval for the parameter. I also accept that bootstrap methods may be impractical for routine use but if the parameter is really critical e.g. Emax during drug development, then resources spent on bootstrap may be more cost-effective than relying on asymptotic SEs with the unlikely assumption that the confidence interval is symmetrical. My comments about SEs not being worth much should be interpreted in the context of the application of using the SE and what value arises from that. For most modelling projects I have been involved in it is very unusual for the the project owner to have demonstrated any value from knowing the SEs.