              The least-squares goodness-of-fit parameter S for reflection data\
               classified as 'observed' (see _reflns.observed_criterion), after\
               the final cycle of refinement. Ideally, account should be taken\
               of parameters restrained in the least squares. See also the\
               definition of _refine.ls_restrained_S_obs.\
\
                   ( sum|w |Y~obs~ - Y~calc~|^2^| )^1/2^\
               S = ( ---------------------------- )\
                   (       N~ref~ - N~param~      )\
\
               Y~obs~   = the observed coefficients\
                          (see _refine.ls_structure_factor_coef)\
               Y~calc~  = the calculated coefficients\
                          (see _refine.ls_structure_factor_coef)\
               w        = the least-squares reflection weight\
                          [1/(e.s.d. squared)]\
\
               N~ref~   = the number of reflections used in the refinement\
               N~param~ = the number of refined parameters\
\
               sum is taken over the specified reflections