Re: st: statistical significance in a data set with weightedobservations

["Sarah A. Mustillo" <smustillo@psych.mc.duke.edu>]

Hi -

I may be joining this conversation too late, but you mentioned fweights in 
this message, and Laurel was talking about pweights in her earlier response 
to you.  Do you know which kind of weights you have?  fweights are very 
different than pweights, and so it is extremely important to know which one 
you have before you can figure out how to account for it in a t test. The 
Stata User's Guide explains the difference types of weights, if you don't 
know this already.

Sarah

--On Friday, May 23, 2003 3:31 PM -0400 mmelnik@mindspring.com wrote:


> Thank you!
>
> I do account for the weights using fweights in my regression, but the
> weights increase the impact of observations, and thereby impacting the
> t-statistics making the effect that all explanatory variables are
> significant. Is there a way of accounting for that effect on t-stats?
>
> thanks,
>
> Mikhail
> ----- Original Message -----
> From: "Copeland, Laurel" <Laurel.Copeland@med.va.gov>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Friday, May 23, 2003 3:05 PM
> Subject: st: RE: statistical significance in a data set with weighted
> observations
>
>
> > The data can be weighted to reflect the sampling design.  The sampling
> > design is complex to give you a sample that is representative of the
> > underlying population, and to allow inferential statistics.  The complex
> > sampling lets you get a good sample of a large population of unlisted
> > smaller units (e.g., all US residents), based on a complete list of
> > larger units (e.g., US census tracts).  The weight is the inverse of the
> > probability of getting sampled.  In your sample, individual units had
> > differing probabilities of being sampled, so they have differing weights.
> > The calculated size of the population that is represented by your sample
> > will be produced by Stata -svy-- commands. To analyze such a sample
> > properly, you must include the PSU, strata, and weights in your analysis,
> if
> > they exist. Without the weights, the estimates you get will be biased.
> > Sometimes weights are used to allow post-stratification (for matching to
> > a known distribution) or to deal with non-response.
> > -Laurel
> >
> > -----Original Message-----
> > From: mmelnik@mindspring.com [mailto:mmelnik@mindspring.com]
> > Sent: Friday, May 23, 2003 2:52 PM
> > To: statalist@hsphsun2.harvard.edu
> > Subject: st: statistical significance in a data set with weighted
> > observations
> >
> > Dear Stata Users,
> >
> > I have encountered this small problem and since I am not sure about how
> > to address it myself I've decided to ask you all. Thank you in advance
> > for
> any
> > advice you might have for me.
> >
> > I am working with a dataset that has weights for all observations, and
> these
> > weights exhibit large variation, from 1 to over 500. When I run a
> > nonweighted estimation my t-statistics are relatively small, but when
> > weights are introduced, the t-statistics jump. Is there a way of
> determining
> > the true statistical significance of coefficients in this case?
> >
> > Thanks again for any help you might have,
> >
> > MM
> >
> > *
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Sarah A. Mustillo, Ph.D
Department of Psychiatry and Behavioral Sciences
Duke University School of Medicine
Box 3454
Durham NC 27710

919 687-4686 x241
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