Comparing the part with the whole: should overlap be ignored in public health measures?

Abstract

The overlap may not be of concern if the result is significant or if the subgroup is <10% of the whole population, but if the overlap is greater than 10% it should not be ignored. The easiest way of allowing for overlap is to use a correction factor, calculated from the amount of overlap, to adjust analyses that ignore overlap.