RE: WRES AND OUTLIER IDENTIFICATION/EXCLUSION

From: "NIYI ADEDOKUN" niyiadedokun@hotmail.com Subject: RE: [NMusers] WRES AND OUTLIER IDENTIFICATION/EXCLUSION Date: Tue, 26 Sep 2006 14:19:20 +0000 Many thanks for responses to this posting. Clearly "true" outliers may give important information in model building but suspected "errors" in data can be very detrimental to convergence as well as a succesful covariance step. I have noticed this phenomenon when using FOCEI. Runs with FO or FOCE would converge with the data 'errors' while with FOCEI convergence is only possible when the data errors are excluded. I suspect that sensitivity to data errors is estimation method dependent. More bothersome is the fact that when convergence does occur with FOCEI, parameters could differ by as much as 25%. Since I have more confidence using FOCEI one is left to make a decison on what to do with the data "errors". As for comparing models with and without the 'errors', how can one compare parameters obtained from a converging and a non converging NONMEM run? In addition if one were to use CWRES as a diagnostic to exclude data "errors" what would be the acceptable cut off point? Regards Jo