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Re: st: svyset for survey with oversampling


From   千早 ケンジ <chihayakenji1893@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: svyset for survey with oversampling
Date   Sat, 22 Aug 2009 02:22:34 +0900

Hi Cam,

Thank you for your reply. They do provide a weight variable to use when analysing the samples together to correct for urban population oversampling, but I believe that it is not taking in to account the other biases introduced by the multistage sampling.

It would be nice if there was a solution that allowed me both to correct the biases of multistage sampling and of oversampling of the urban population.


Guilherme

On 2009/08/22, at 2:12, Cameron McIntosh wrote:

Hi Guilherme,
They don't provide some adjustment to the sampling weights to allow for combined analysis?
Cam

----------------------------------------
From: chihayakenji1893@gmail.com
To: statalist@hsphsun2.harvard.edu
Subject: st: svyset for survey with oversampling
Date: Sat, 22 Aug 2009 02:00:35 +0900

Dear Statalist Members

It is my first post to this list. My name is Guilherme Kenji Chihaya
and I am currently a graduate student in Tohoku University, Japan. I
am using a data set called Life Histories and Social Change in
Contemporary China. It is a survey in which the rural and urban
populations of China were treated as different populations and each
one was sampled for about 4000 samples using multistage sampling with
clustering.

The proportion of China's rural population was about 70% by the time
of the survey, however, this survey is designed so that it accounts
for 50% of the whole sample if you try to analyse the two samples
together. Besides this problem, it still has all the other biases
caused by multistage clustering.

I wonder if it is possible to use svyset to correct all these biases
so that I can analyse the two samples as one single dataset. The
codebook for the survey is incomplete, it states that the data is
supposed to be analysed using Stata complex samples functionality but
the part about how to use it is unfinished in the available version.
There are variables identifying the primary sample unit and the
stratum used for sampling. However, I don't know how to deal with the
rural-urban disproportionality.

I would appreciate if someone could help me with this, especially if
there is anybody in this list that is familiar with this dataset.

Guilherme Kenji Chihaya

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