Re: Bootstrap analysis

Varsha, Congratulations on discovering how to use a bootstrap to evaluate the distribution of your model parameter estimates. The bootstrap mean is probably a more robust estimate of the true value of the parameter than the value estimated from the original data. I prefer to report the bootstrap mean for this reason. The uncertainty, e.g. 95% confidence interval, can sometimes be useful for model evaluation but more commonly is is best used to keep journal reviewers 'happy'. There are very few other real applications of knowing the uncertainty of a single parameter but it might be used to try to demonstrate that a PD parameter (e.g. Emax) is different from zero and thus indicate that the drug does something useful. The good news is that you don't have to worry about using bootstraps "to confirm the fact that the model I have is the best fit for the data". The bootstrap can never confirm this for you. You need to buy a subscription to 'Talk to God' in order to get that kind of information. Nick Varsha Mehta wrote: > Group: > > I have bootstrap analysis (my first) parameter estimates and model > parameters. The PDxPOP/NONMEM manual I have does not provide > any guidance as to how I can statistically compare these two (or do I > need to?). I also have histograms for the thetas in bootstrap analysis. > I can make some visual judgements but is there a way to statistically > compare the two results (bootstrap v model) built in to the NONMEM > that I can use to quickly get some statistical comparison results? > > How else can I use the bootstrap results to confirm the fact that the > model I have is the best fit for the data? > > Thanks in advance. > > Varsha Mehta, MS(CRDSA), Pharm.D., FCCP > Clinical Associate Professor > Pharmacy, Pediatrics and Communicable Diseases > Clinical Pharmacist Neonatal Critical Care > University of Michigan > (O) 734-936-8985 > (F) 734-936-6946 > [email protected] > > ********************************************************** > Electronic Mail is not secure, may not be read every day, and should not be > used for urgent or sensitive issues -- Nick Holford, Dept Pharmacology & Clinical Pharmacology University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand [email protected] tel:+64(9)923-6730 fax:+64(9)373-7090 mobile: +33 64 271-6369 (Apr 6-Jul 17 2009) http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford