| Re: Pooling 3 rounds of DHS Nepal -- weights? [message #19660 is a reply to message #19651] |
Mon, 27 July 2020 17:45  |
LeahBevis
Messages: 6
Registered: October 2019
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Hello,
Thanks for the response. Yes, we converted those dates. I realized that the problem is actually the 2016 strata.
We are working only with the districts in the Terai region of Nepal -- the southern-most districts along the Indian border.
In 2006 and 2011, the 13 strata contain 5 strata that uniquely defined the Terai, allowing us to have a representative Terai sub-sample. Great.
But in 2016 the stratification changed: now 10 strata define the urban and rural parts of the 5 provinces shown in the attached map. The problem is, that leaves us with very few PSU in the Terai part of the rural/urban strata of Provinces 3 and 4 -- circled in yellow on the map. In Province 3, only 1 rural PSU exists, and this is why Stata can't use svyset with those strata. However, only 4 urban PSUs exist in Province 3, and only 3 rural and 3 urban PSUs exist in Province 4. And I don't understand how Stata's svyset interprets weights with respect to their stratum, so I don't know if these very-few-PSU-strata are a problem.
So, ideally, I want our sample to be representative of the Terai. I realize that's not possible with the 2016 sampling strategy, but how should I best deal with the PSUs in Provinces 3 and 4, in order to be as close as possible? Should I...
--- Drop the single rural PSU in Province 3 and proceed as normal?
--- Re-assign Province 3 IDs to Province 2 IDs (since Chitwan is next to Province 2) and re-assign Province 4 IDs to Province 5 (since Nawalpur is next to Province 5)? This seems geographically logical, but is a bad idea if weights are properly interpreted only w/ respect to their correct stratum.
--- Something else?
Thanks in advance for your advice.
Leah
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