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Re: st: oversampling correction
From 
 
Steven Samuels <[email protected]> 
To 
 
[email protected] 
Subject 
 
Re: st: oversampling correction 
Date 
 
Thu, 11 Nov 2010 13:33:12 -0500 
-
Nicola, look up the sections on weights in a good sampling book, for  
example Robert Groves et al., Survey Methodology; Sharon Lohr,  
Sampling: Design and Analysis;  Chapter 16 of Levy & Lemeshow,  
Sampling of Populations.
Steve
On Nov 11, 2010, at 12:30 PM, Stas Kolenikov wrote:
There was a paper in the most recent issue of Stata Journal doing
exactly what you need. See
http://stata-journal.com/article.html?article=st0196. 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
weights.
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 http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.
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