| Regarding de-normalizing and weighting procedures in Stata [message #9538] |
Mon, 11 April 2016 06:47  |
AmsP
Messages: 24
Registered: April 2016
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Member |
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Hello,
I'd like to ask for help about if my procedures to de-normalize and weight data in Stata are correct. I just want to calculate average schooling years of women (older than 30) in urban region whose schooling year is above the average level of all women in the survey.
Step 1: De-normalize each survey (various years) of the same country by "gen v005_denorm=v005*(number of 15-49 aged women in the country in the survey year)/(number of 15-49 women surveyed in this survey round)". After de-normalizing each dataset, I append them together to have a single big survey dataset for this country.
Step 2: gen wgt=v005_denorm/1000000
Step 3: mean v133 [pweight=wgt]
step 4: mean v133 if v133>mean & v025==1 & v012>30 [pweight=wgt] "Here, shall I still add [pweight=wgt]?"
Because I just need a single mean schooling value (for later regressions), I do not think that I need cluster and strata adjustment. Am I right?
But if I do cluster and strata adjustment, then the procedures will become:
Step 1 and 2: the same as above for de-noemalizing, appending and dividing v005_denorm by 1000000
Step 3:gen psu=v021
gen strata=v023
svyset psu [pweight=wgt], strata(strata)
Step 4: svy: mean v133
Step 5: svy: mean v133 if v133>mean & v025==1 & v012>30
The two methods generate the same result (I do not need to consider standard error, so I prefer the first method without cluster/strata adjustment).
Thank you very much in advance!
[Updated on: Mon, 11 April 2016 06:57] Report message to a moderator |
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