In sci.stat.edu John Hendrickx <[EMAIL PROTECTED]> wrote:
[snip]
: There is also some debate on using weights for stratified sampling and/or
: to correct for sampling bias. Weighting leads to correct estimates but
: incorrect standard errors.
Weights often get blamed for things that are not their fault. In the situation
described, the "standard errors" coming out of traditional software will be wrong
with or without weights. [If one just wants "ballpark" standard errors, adjust
the weights by dividing them by their average.]
: One solution is to include the design
: variables in the model instead of weighting. Stata and Wesvar are two
: programs that can take weighting into account when calculating standard
: errors of estimates.
Agreed.
--
Michael P. Cohen home phone 202-232-4651
1615 Q Street NW #T-1 office phone 202-219-1917
Washington, DC 20009-6310 office fax 202-219-1736
[EMAIL PROTECTED]
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