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Re: st: oversampling correction

From   Stas Kolenikov <[email protected]>
To   [email protected]
Subject   Re: st: oversampling correction
Date   Thu, 11 Nov 2010 11:30:11 -0600

There was a paper in the most recent issue of Stata Journal doing
exactly what you need. See It has its own
set of ideas in mind, but I am sure you'll be able to twist its hands
to produce weights calibrated to your totals, means or fractions
(there's an example in the paper to help you out with that). Out of
all the sampling design intricacies, you would only need to specify

On Thu, Nov 11, 2010 at 9:41 AM, Nicola Baldini <[email protected]> wrote:
> I repeatedly read some authors whose surveys received replies from a sample somewhat different from the population reporting that they corrected for oversampling. What does it mean (i.e. can I do the same in Stata and how)? I thought it was so simple I cound find a solution in the FAQ, and also a search on previous posts did not provide a statisfying reply (may be this is because my survey is so simple that does not have a sampling design). Indeed, I have a universe of 710 individuals, but I could find the emails for sending my survey only for 510 (my population) and I received a reply only from 210 (my sample). The survey is a 12-item 5-point Likert scale from 1 to 5. The statistical analyses include -ttest-, -anova- and -factor- on Stata 9.2
> PROBLEM 1: Women are 26.5% in the population but only 16.3% in my sample: how can I correct for this?
> PROBLEM 2: The population is divided in 10 organisations of unequal size, and each organisation is divided in 2 groups of unequal size (or it is the reverse: there are two groups of unequal size - e.g. based on traveling at least once in a life to Africa or not -, and group members may belong to 10 organisations). The response rate varies at the organisation and at the group levels: can I correct for this? and how? Can I transform the data so that I have the same number of respondents in each group (e.g. 5 respondents per group x 2 groups x 10 organisations = 200 respondents)? Also: can I transform the data so that I have the same response rate (e.g. 40%) in each group?

Stas Kolenikov, also found at
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