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India Weights SAS and Merging [message #16014] Mon, 22 October 2018 00:48 Go to next message
pmontine@gmail.com is currently offline  pmontine@gmail.com
Messages: 1
Registered: October 2018
Member
I looking at tobacco usage and tuberculosis in adults in India 2015-2016. I have two questions.

1. I am using merged data from India 2015-2016. I have successfully combined the HIV, men, women and household members tables together. I thought to use mv005 and v005 as weights and just combining them together. Should I use the hv005 as my weight instead? I wasn't sure which one to use.

2. I am using SAS and after watching the video provided by DHS on how to set up the code I attempted to weight the data. The problem was that my numbers were still about the same as the original numbers. The weights were not giving the whole population of India. I put the code below that I was using. I wasn't sure what I was missing.

proc surveyfreq data=women;
table v025;
weight wgt; (v005/1000000)
cluster v021;
stratum v022;
run;

Thanks so much.
Re: India Weights SAS and Merging [message #16057 is a reply to message #16014] Wed, 31 October 2018 09:59 Go to previous message
Trevor-DHS is currently offline  Trevor-DHS
Messages: 787
Registered: January 2013
Senior Member
1) In general, we at DHS would use hv005 for an analysis limited to variables in the PR file. if you are including IR variables, use v005; if MR variables (or the CR file) use mv005; if domestic violence variables, d005; if HIV prevalence, use hiv05. These respective weights are similar but are adjusted for non-response by the different kinds of respondents.

2) Weights in DHS are normalized to the unweighted number such that the total weighted number of households, women or men are the same as the unweighted number of households, women or men when applying the appropriate weight (hv005, v005, or mv005 respectively). DHS does not estimate population counts, rather proportions of the population. If you want to calculate population counts, you can create a factor to inflate the sample by multiplying by the total population divided by the total sample of de jure household members.
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