Pat,

I'm no expert on this, but here's a simple approach:

You had 1,025 respondents.

You wanted 42.5% of them to be FT (N=589), but you got 59.7% FT, N= 612 .So the weight for FT students in you sample is 589/612, or 0.9624 You wanted 57.5% of hem to be PT (N=436) ,but you got 40.3% FT, N= 413 . So the weight for PT students in you sample is 436/413, or 1.0557

SAS: if time = "full' then casewt = 0.9624; if time = "part' then casewt = 1.0557

then in your PROCs, include the weight statement: weight casewt;

Check your N's - in some PROCs N's get adjusted (FREQ?) and in others they don't (MEANS?). Not sure about TABULATE.

Hope this is at least a start

As for the lay audience - "Data were weighted so respondent's (enrollment status) characteristics would mirror that of our student bod." (?)

I'd be interested to hear what others think.

-Michael

At 02:18 PM 2/19/2004, Pat Moore wrote: >There is a SAS question further down in this missive, but I need to lay on >some background first. ... snip

>My dataset consists of the responses of 1,025 students to a set of 116 >questions. I'm using proc tabulate to generate the mean responses of the >subjects to the 100 non-demographic questions. >I'm also going to have to explain the weighting process to a lay audience >so they can judge if it is a valid way to look at the findings. > >As always, I appreciate the list and the wonderful help you all give me. > >Pat Moore

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Michael Whitcomb Assistant Director of Institutional Research Wesleyan University 237 High Street, 305 North College Middletown, CT 06459-0280

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