Is there any way to get a good sense of how much missing data invalidates analysis, that is when you have to question your model? For example I would guess that at worse we might lose 2 percent of our cases in a multivariate regression (no one variable would have 2 percent missing, 2 percent of the cases will be missing some data on different variables when means the regression excludes that case)?