Re: LLR test, AIC, BIC

From: Nick Holford n.holford@auckland.ac.nz Subject: Re: [NMusers] LLR test, AIC, BIC Date: 10/21/2003 8:31 PM David (the other), My advice is not to waste your time with AIC, LLR etc if you are using NONMEM. If you want to know the true null distribution for an objective function change then you should be prepared to estimate it using the randomization test. In your example this means fitting the original data with a one compartment model and a two compartment model and recording the delta OBJorg. Then use the one compartment parameter estimates to simulate say 1000 data sets (the randomization part). Fit each of these data sets to a one compartment model and a two compartment model. Look at the distribution of the 1000 delta OBJ values to find the probability that you would have observed delta OBJorg under the null hypothesis. This is an estimate of the true P value for falsely rejecting the null (the test part). Whether the time spent doing the randomization test is a better waste of time instead of worrying about AIC, LLR etc. is up to you Nick Nick Holford, Dept Pharmacology & Clinical Pharmacology University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand email:n.holford@auckland.ac.nz tel:+64(9)373-7599x86730 fax:373-7556 http://www.health.auckland.ac.nz/pharmacology/staff/nholford/