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I am working with some Census data that comes from a survey. There is a weight variable, given that they use a fairly complex sampling scheme to ensure adequate representation from different groups. I am aware that JMP will compute weighted averages when analyzing distributions, if I put the weight variable in the Weight box of the dialog. I am also aware that JMP ignores the weight variable when analyzing the distribution of a nominal variable. But it is not clear to me why. In particular, I am wondering what the correct way is to describe the distribution of a nominal variable. For example, suppose there are two groups and group 1 comprises 40% of the total respondents. Suppose that group 1 variables have 60% of the total weights. Analyze distributions will show 40% in group 1. If I put the weight variable in the Frequency box, then group 1 will comprise 50% of the total. Which is the correct fraction in group 1? Is it the raw % or the percent weighted by the frequency of the weights? And, if it is the latter, why isn't it handled by putting weight in the Weight box, rather than the Frequency box?
Thank you for attempting to address my question - but your response is a bit too cryptic for me. The JMP documentation did not help - it just states what I stated in my question. Weights can be used for continuous variables, but are ignored for nominal variables. I don't understand your statement regarding "historical reasons." What are these? From the other cites you provided, I suspect this has something to do with sas rather than jmp. I'm not a sas user, so I wouldn't know. Just say what you mean.
More to the point, are you confirming that when you have survey weights, they should be cast in the frequency role for nominal variables, but in the weight role for continuous variables? That is what I have come to believe, but I'd appreciate some confirmation of that, even if the "historical reasons" must remain obscure.