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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]
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USA
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