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Re: st: combining multiple surveys - adjustment of weights
From
Steven Samuels <[email protected]>
To
[email protected]
Subject
Re: st: combining multiple surveys - adjustment of weights
Date
Fri, 28 Jan 2011 11:42:39 -0500
Oops: Example where this was _not_ the case:
I should clarify point 1. I meant, there is no statistical problem if
all primary sampling units are defined in the same way. Example where
this was not the case: In some of our surveys of businesses, in some
areas, there was a listing for each location where a business
operated; in other areas, there was a listing only for each parent
business, but not for the separate locations.
Steve
On Jan 28, 2011, at 9:04 AM, Steven Samuels wrote:
On Jan 27, 2011, at 11:45 PM, Dana Shills wrote:
> I am trying to combine multiple country survey datasets (10
surveys) to
> estimate ols regressions of firm performance across the 10
countries. 8 of
> the surveys are stratified random samples of firms in the 8
countries (so
> the strata identifier in each dataset goes from 1 to some number N,
that
> varies) and 2 others are simple random samples. The survey
questionnaire
> is the same across countries.
> 1> Statistically are there any issues with combining multiple
surveys when
> the sampling methods are different?
Not if the primary sampling units were the same in all surveys.
> 2> To declare the combined dataset in Stata as a survey, I create a
new
> strata variable that doesn't overlap between the surveys (as
suggested in
> the previous thread). But how should I deal with the probability
weights
> provided in each dataset?
See below.
> Suppose I assume that the sum of the weights in each country
(countrysum)
> represents the population, then can I just rescale each weight by
(sum of
> weighs across all countries)/countrysum?
Don't assume: Check! If the weight sum in each country is
approximately or exactly equal to the population size (number of
firms), don't rescale. Use the weights as given.
(Modification: if you know the population sizes exactly and had <100%
response, you might apply non-response adjustments. With SRS, the
simplest is to create a new weight= N/n' where N is the known
population size in the stratum and n' is the achieved sample size.
For other methods, see section 8.5 of Sharon Lohr, Sampling: Design
and Analysis, 1999 or 2010 editions, Brooks/Cole, Boston.)
> 3> I am running weighted regressions using the svy: regress command
on the
> combined dataset. If the sample size varies greatly between the
surveys,
> should I rescale each firm level variable in the regression by the
sample
> size in that country or does svy take care of this?
Stata's survey commands will take care of it.
Steve
Steven J. Samuels
[email protected]
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax: 206-202-4783
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