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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.


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.


Steven J. Samuels
[email protected]
18 Cantine's Island
Saugerties NY 12477
Voice: 845-246-0774
Fax:    206-202-4783

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