>>(i) We have multiple observations of the same, already integrated h: the >>'unmerged' data <- most important data set which SHOULD BE deposited and >>rarely is.
>yes, fully agree. Perfect. > I don't quite understand the difference between (ii) and (iii). As soon as > you take the weighted average, you merge the data, because you create one > single estimate of the intensity I (and sigma(I)) of a unique reflection from > several symmetry-related observations of that unique reflection. So, to me, > 'taking the weighted average' and 'merging' are different words for the same > procedure. There is indeed no distinction between (ii) and (iii) form the merging point of view, I just wanted to point out the difference between just 'merged' and 'unique' data. We return to Kay's original post. >> Indicators of precision of *unmerged* data are: [Rsym=Rmerge (which should >> be deprecated),] <- yes, and I want to iterate: Here is already where the notational confusion starts - 'unmerged' data (i) obviously contain multiple observations of a single reflection h, then how can any measure of their quality logically be called an Rsym (there is no sym in a single reflection) ? A Rsym is per definition of sym a measure producing merged data of type (iii) , although it is also AN Rmerge. Historically this seems to come from the original Arndt definition (c.f. Diederichs & Karplus 1997) but it is illogical in the above context. The original definition of Rmerge also includes already the summation over a set of binned hkls. Along the same line, that the quality indicator for 'unmerged' data is their 'merging' R is also illogical - they have the same quality before they are merged. Not only as a statistic, even as a term Rmerge should be buried (i.e. finally BECOME a statistic). One primary statistic that is valid universally are the <i/sigI>. None of these Rs are robust statistics. Rmeas is an asymptotic target (penalizing you for small N) , and Rpim some form of standard error of the mean (rewarding you for large N). Choose wisely.... Because of its statistical defensibility (clear definition and the association with a confidence or significance level) CC1/2 is interesting and perhaps the only measure in addition to primary <I/sigi> needed - with the juicy bonus of having via CC*/work/free a traceable relation to the model quality. That, as Kay has pointed out in his papers, is more than you can say about any of these Rs. </anti_R_flame> > Thus, Rmerge � 0.8/<I/s(I)> can only hold for unmerged data (i.e. observations), not for merged data (unique reflections, after averaging over symmetry-related observations). True. I see that. Which is the reason why it is still close for the low redundancy data historically observed, but I think this will change rapidly with the PADs & high redundancy becoming standard - another reason to bury Rmerge & associates. Happy Easter, BR best, Kay > >Is that correct? If so, let�s continue the thread (there is more to come...) >or adjust the definitions. > >Best, BR
