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

 From "Sarah A. Mustillo" <[email protected]> To [email protected] Subject Re: st: statistical significance in a data set with weightedobservations Date Fri, 23 May 2003 15:48:23 -0400

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 [email protected] 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" <[email protected]>
To: <[email protected]>
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
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: [email protected] [mailto:[email protected]]
Sent: Friday, May 23, 2003 2:52 PM
To: [email protected]
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
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?

MM

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```
```*
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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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*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/
```

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