Re: LLR test, AIC, BIC

From: "Bonate, Peter" pbonate@ilexonc.com Subject: Re: [NMusers] LLR test, AIC, BIC Date: 10/23/2003 8:43 AM David, I don't know if you ever got anybody to answer you. But The AIC was originally predicated on independent observations, like in linear regression. I am not sure if it was ever really validated for repeated measures data, but people do it all the time. NOBS is total number of observations. NPAR is the number of estimable parameters, all thetas, etas, and sigmas, including covariances. BIC tends to pick the simpler model more often than AIC or AICc. The AICc was for small sample sizes and I don't believe really applies to pop pk models. NOBS is usually much larger than NPAR, so the second-order correction term is practically zero. An excellent book on this is Model Selection and Inference by Burnham and Anderson. This is a must read. Hope this helps, pete bonate