RE: WRES AND OUTLIER IDENTIFICATION/EXCLUSION

From: "Xiao, Alan" alan_xiao@merck.com Subject: RE: [NMusers] WRES AND OUTLIER IDENTIFICATION/EXCLUSION Date: Tue, 26 Sep 2006 10:37:08 -0400 I think the key is when to exclude the "outliers". If they are excluded at the beginning, you might lose some important information about your drug (and consequently important findings) as Mike mentioned below. If they are excluded after you got a final model and you want to refine the final model with the exclusion, you then lose much less information - you can not really well characterize the lost part anyway since your model can not capture them either because they are simply data errors or non-representativeness for a new population or other reasons you can imagine, although you still need an interpretation about the "outliers". In this case, your refined final model might be more reliable to data which are representative, but not covering the outliers. Appropriate documentation and interpretation (and implication) are very important. Alan