Re: FW: PPC

I cannot make any general statements but here is the summary of the 13 different models that I tested for comparison of bootstrap and nonmem CI. http://www.quantpharm.com/pdf_files/2572-GibianskyPage2007Poster2007final.pdf Note that all bootstrap samples were appropriately stratified by major covariates (such as study, dose, weight as necessary, etc.). Leonid -------------------------------------- Leonid Gibiansky, Ph.D. President, QuantPharm LLC web: www.quantpharm.com e-mail: LGibiansky at quantpharm.com tel: (301) 767 5566 [EMAIL PROTECTED] wrote: > Dear Dr. Holford, > > Please correct me if I am wrong, however my understanding is that asymptotic distribution implied by NONMEM's covariance step approaches normality as the sample size gets larger or we have more data. However, a non parametric bootstrap distribution may have poor coverage with a small sample size as well, since it relies on sampling subjects with repalcement in the data set. So both distributions have problems when sample size is small (e.g. N<30). Therefore I would think when N is large the wald based Confidence Intervals from NONMEM are appropriate enough. It would be helpful to know the criteria when generating a non parametric bootstrap distribution is really advantageous. > > Thanks, Mohamed > Quoting Nick Holford <[EMAIL PROTECTED]>: