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using design elements correctly [message #25832] |
Fri, 16 December 2022 03:42  |
gebretsh@gmail.com
Messages: 17 Registered: June 2022
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Member |
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Dear Dr Tom and other DHS experts,
I'd like to thank you for your usual invaluable firsthand assistance with DHS data analysis.
I would like now to ask questions on the specifications of the three design elements of DHS data: cluster, weight and strata
1) I have a habit of using these three elements whenever I do analysis using DHS data via the svyset function in Stata.
svyset psu [pw=weight], strata(strata var) singleunit(centered)
Now, I read today the Stata's survey data reference manual and recommends the specification of a secondary sampling unit (ssu), which is the household ID in DHS, as follows:
svyset psu [pw=weight], strata(strata var) || household Id (v002)
I have already analyzed my data using the first command and sent it to a journal for publication. Should I re-analyze the data using the second code?
2) I want to use a Stata command that does not support "svy". The Stata command that I want to use is "mvdcmp", a tool used to do decomposition analysis between two groups. Now, In place of the svy command, I just opt to use another way of supplying the design elements into my syntax, as follows:
mvdcmp place of residence: logit skilled_onc_2days wealth_early1 wealth_early2 [pw=w1], robust cluster(id)
To add to the problem, this "mvdcmp" command does not support/accept strata, and supports only weight and cluster, as indicated above. Is there a severe problem If ignore the strata variable from being taken into account in my analysis.
Thanks so much for your advice.
Regards,
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Re: using design elements correctly [message #25836 is a reply to message #25832] |
Fri, 16 December 2022 11:04   |
Bridgette-DHS
Messages: 3230 Registered: February 2013
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Senior Member |
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Following is a response from Senior DHS staff member, Tom Pullum:
We recommend the version of svyset that you are currently using. I just ran the lines below on the Philippines 2017 DHS, for an example. #1 includes only the weights, v005. #2 adds the usual adjustments for clustering and strata with svyset. #3 is your proposed modification of svyset, with subsampling of households.
All three models give exactly the same estimates of coefficients. #2 and #3 give estimates of standard errors, test statistics, and confidence intervals that are different from #1. However, the estimates of standard errors, etc. are exactly the same in #2 and #3. That is, you can use #3 if you want but it appears from this simple check that the results will be the same as with #2.
Note: I am not proposing that you would analyze CEB with linear regression! This is just an example of a statistical model.
* Estimation #1
regress v201 i.v013 i.v190 [pw=v005]
* Estimation #1
svyset v001 [pw=v005], strata(v022) singleunit(centered)
svy: regress v201 i.v013 i.v190
* Estimation #1
svyset v001 [pw=v005], strata(v022) || v002
svy: regress v201 i.v013 i.v190
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