Guidance regarding Gender Pooling in Liberia 2013 DHS data [message #19992] |
Fri, 11 September 2020 13:54 |
Miatta
Messages: 3 Registered: September 2020
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I am examining HIV testing behavior among men and women in Liberia, West Africa. 2013 Liberia Demographic and Health Survey men and women dataset: I would like to inquire about appending the men and women (unmarried persons) datasets together.
My question is how do I create accurate pooled weights (2013 Liberia DHS men and women data)? Do I need to also create a pooled strata and primary sampling unit (psu)? If so, any guidance will be appreciated. Many of posts in the forum discuss pooling multiple countries or years together but I am seeking guidance regarding gender pooling. What modifications will I need to make to the weights to get accurate results once the data has been appended? Thank you
Best, Miatta Dennis
Georgia Southern Univ DrPH Candidate
[Updated on: Fri, 11 September 2020 13:59] Report message to a moderator
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Re: Guidance regarding Gender Pooling in Liberia 2013 DHS data [message #19993 is a reply to message #19992] |
Fri, 11 September 2020 18:28 |
Bridgette-DHS
Messages: 3214 Registered: February 2013
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Senior Member |
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Following is a response from DHS Research & Data Analysis Director, Tom Pullum:
You don't need to alter the weights at all. I would open the men's file, then enter "rename mv* v*" and "gen sex=1", then append the women's file, and enter "replace sex=2 if sex==.", "label define sex 1 "Man" 2 "Woman" " and "label values sex sex". I would define sex to be consistent with hv104 in the PR file. The IR labels will over-write the MR labels in the append because the last file in any set of appends will determine the variable and value labels. You should check your key variables; some may be different in the IR and MR files, which case you want to keep them as separate v and mv variables.
The weights in the two files have already been normalized to have a mean of 1 (1,000,000 with the usual factor). If you combine the files as described, the number of cases in the two files will differ, and that will accurately convey the different numbers of men and women in the household population, as identified in the PR files. The weights in the IR and MR files have also already been adjusted for any nonresponse (loss of cases when going from the PR file to the IR and MR files). For svy purposes you don't need to change the cluster or strata ID codes. So it's much simpler than pooling surveys from different countries or time periods.
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