Jackie I agree completely with Ed (for once!), not only for the reasons he gave, but also that it's valid to compare statistics such as likelihood and R factors ONLY if only the model is varied. Such a comparison is not valid if the data used are varied (in this case you are changing the data by deleting some of them).
Cheers -- Ian On Tue, Oct 26, 2010 at 2:37 PM, Ed Pozharski <[email protected]> wrote: > Jackie, > > please note that (at least imho) the desire to obtain "better" R-factors > does not justify excluding data from analysis. Weak reflections that > you suggest should be rejected contain information, and excluding them > will indeed artificially lower the R-factors while reducing the accuracy > of your model. > > Cheers, > > Ed. > > On Mon, 2010-10-25 at 17:44 -0400, Jacqueline Vitali wrote: >> Also if your Rmerge is high and you include all reflections in >> refinement, Rfree is high. In my experience, by excluding F < sigma >> reflections you drop Rfree a lot. > > > > -- > "I'd jump in myself, if I weren't so good at whistling." > Julian, King of Lemurs >
