Home » Countries » Kenya » Kenya DHS weights (Kenya DHS weights)
| Re: Number of respondents [message #29887 is a reply to message #29884] |
Fri, 16 August 2024 12:26   |
Bridgette-DHS
Messages: 3199
Registered: February 2013
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Senior Member |
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Following is a response from Senior DHS staff member, Tom Pullum:
The weights compensate for the over-sampling of clusters in smaller strata and the under-sampling of clusters in larger strata, as well as for variations in the number of vacant households and non-response. That's why the weighted numbers are more representative than the unweighted numbers. All households within a cluster have the same weight. All individuals within a cluster have the same weight.
In (a), there is NOT an assumption that all household members are in school. Don't worry about that.
For (b), I would say there are 2 ways to rank the counties. Both of them use weights. You can rank them in terms of the number of students currently attending, or in terms of the percentage of eligible students who are currently attending. The following lines do this, using the PR file for the 2014 survey. I use the "collapse" command. There are alternatives, but this seems the easiest.
use "...KEPR72FL.DTA", clear
* measure of school attendance: sh18, "attend school current year"
* county list: shregion
gen cases=1
gen inschool=1 if sh18==1
collapse (sum) cases inschool [iweight=hv005/1000000], by(shregion)
* sort the counties by number currently attending
sort inschool
gen cases_rank=_n
list, table clean
* sort the counties by current attendance rates
gen inschool_pct=100*inschool/cases
sort inschool_pct
gen rate_rank=_n
list, table clean
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Current Time: Sat Nov 30 07:27:01 Coordinated Universal Time 2024
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