| Normalizing weight for region/province [message #2178] |
Sun, 18 May 2014 02:57  |
jcon
Messages: 3
Registered: May 2014
Location: United States
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DHS normalizes weights so that the national unweighted n = weighted n.
The province/region sampling error tables show both unweighted and weighted n, with the weighted n normalized at the national level. This means that in some oversampled provinces the weighted n is very small. Are province/region level confidence intervals calculated with the weighted or unweighted n?
I am doing an endline evaluation for a project that covered three provinces in Lao PDR. The baseline is the 2011/12 MICS/DHS (combined). Currently, I'm trying to estimate power/sample size for comparing baseline to a future endline. I need to keep the sample weighted so that it is representative at the provincial level, but with the DHS national normalized weights I have an unweighted n of 2200 and a weighted n of 1300 (all of the provinces were oversampled). Can I re-normalize weights so that unweighted n = weighted n in these three provinces? There is no mention of this in the DHS manuals, which only state that provincial level estimates must use weights.
DHS does not normalize to provincial level in any of their tables; always showing the national normalized n at the provincial level. As the sample is representative at province level, it seems like it would make more sense to normalize weights at the provincial level when looking exclusively at specific provinces (something DHS reports are not designed to do).
Any suggestions would be greatly appreciated.
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