| Date: | Wed, 30 Jun 2004 21:55:06 +1200 |
| Reply-To: | DTP <null@VOID.COM> |
| Sender: | "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU> |
| From: | DTP <null@VOID.COM> |
| Organization: | Xtra |
| Subject: | Re: Iterative proportional fitting |
|---|
Zack, Matthew M. wrote:
> It doesn't matter how you construct the matrix of marginal totals,
> TABLE, as long as
> they reproduce the marginal totals of interest. One simple way to do
> so is to assume a model of independence among rows and columns. That
> would imply that each cell in TABLE would equal the following
> expected value:
>
> expected cell value
> in row_i and column_j = (row_i marginal total)*(column_j marginal
> total)/(Table total)
>
> For the cell in row=1 and column=1, the expected cell value would
> equal the following:
>
> (1412)*(3988)/18324 = 307.3, or 307 if rounded to the nearest
> integer.
>
> You can then calculate the values for other 23 cells in this 8-by-3
> matrix, TABLE. Finally, you can modify these values if their rounding
> errors cause the marginal totals of this table
> to disagree with those you ultimately want.
Ah, yes. I'm with you now. I was obviously looking for complications that
weren't there.
Although I can't see why you shouldn't be able to just specify a vector of
the marginal totals, I should be able to manage using the technique you
suggest.
Thanks for the advice.
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