| Re: underfive children HW data: why missing a lot in IR files [message #24192 is a reply to message #24191] |
Fri, 11 March 2022 12:40   |
bun_2019fall
Messages: 9
Registered: August 2021
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Member |
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Hi thank you so much for the detailed response. I replicate your way of tabulation in the PR file and what I observed is consistent with your tabulation/explanation. I did a comparison of PR and IR file, and I am still confuse about the gap between IR and PR files, regarding under-five children and their anthropometric data. Below is the Stata scripts that I used to make the comparison (taking Nigeria as an example).
Briefly, I found that in IR files, there are (way) more under-five children as reported by each interviewed women (I use b8_ to tabulate, which indicates children's current age). In the example of Nigeria, there are more than 30K under-five children. Amongst all these children, a subsample has HW measures - which is correspond with the sample size of children having HC measures in PR files. According to this comparison, it seems to me that:
1.not all under-five children reported in IR files have anthropometric measures
2. all under-five children in PR files have anthropometric measures
My question is that why some under-five children sample in #1 (IR files) were not measured for height and weight? This discrepancy not only exist for this Nigeria file; but I observe similar patterns for other country data as well (at least for the 30+ countries that I am working with). I wonder what documentation I should refer to, in order to resolve this puzzle? Thank you again!!!
clear all
set maxvar 20000
***Nigeria PR file
use "NGPR7AFL.DTA", clear
*total # of underfive children
gen underfive=1 if hc1 < 60
tab underfive
*12,867 underfive
sum hc7*
*12.5K children have hw info
gen momid=hc60
tab momid
*moms not in IR file
recode momid 993/995=.
drop if momid==.
sum hc7*
*recode the invalid hc values
recode hc70 9996/9999=.
recode hc71 9996/9999=.
recode hc72 9996/9999=.
*all underfive children having valid anthropometric data: 11.4k
sum hc7*
*** Nigeria IR file
use "NGIR7AFL.DTA", clear
forvalues i=1/6{
gen underfive`i'=1 if b8_0`i' < 5
}
sum underfive*
keep caseid underfive* hw7*
reshape long underfive hw7_ hw70_ hw71_ hw72_ hw73_ , i(caseid) j(birth)
drop if underfive==.
*30,713 underfive: ALL children
sum hw7*
*recode the invalid hw values
recode hw70_ 9996/9999=.
recode hw71_ 9996/9999=.
recode hw72_ 9996/9999=.
recode hw73_ 9996/9999=.
*underfive children having valid anthropometric data: 11.4k
sum hw7*
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