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Re: st: Using survey weights in regression models
At 09:19 AM 11/24/2003 -0600, Dick Campbell wrote:
I just read this and it is very good. Thanks for recommending it.
Regarding the recent discussion of how to handle
weights in regression, I have found the following
paper to be very informative.
TI: Sampling Weights and Regression Analysis
AU: Winship, Christopher; Radbill, Larry
SO: Sociological Methods and Research, 1994, 23, 2, Nov, 230-257
A key question I still have: One of its key arguments is that most programs
get the standard errors wrong when weighting is used. The article was
written in 1994; is it still true of Stata in 2003? In particular, do the
svy commands (which I have never used) take care of the concerns raised by
To paraphrase their key arguments: Where sampling weights are solely a
function of IVs included in the model (e.g. minorities are oversampled and
race is an IV), unweighted OLS estimates are preferred because they are
unbiased, consistent, and have smaller standard errors than weighted OLS
estimates (because weighting induces heteroskedasticity in the error terms).
Where sampling weights are a function of the DV (and thus of the error
term; oversampling low income groups and using income as a DV would be an
example) unweighted estimates will be biased and inconsistent. The authors
recommend trying a couple of things before you resort to weighting. But in
some cases, weighting will be appropriate, and you should use the White
heteroskedastic consistent estimator for the standard errors. In this
case, weighting will produce consistent estimates of the true regression
slopes; but it will also induce heteroskedasticity in the error terms,
which is why you use White's estimator.
There is other good stuff in the article too, e.g. as was mentioned on the
list before, they suggest comparing weighted and unweighted results as a
check on model specification. Unless I missed it, they don't mention that
standardized coefficients and R-square will be wrong if you don't weight,
so be aware of that if you like to use such things.
Richard Williams, Associate Professor
OFFICE: (574)631-6668, (574)631-6463
WWW (personal): http://www.nd.edu/~rwilliam
WWW (department): http://www.nd.edu/~soc
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