| Re: missing values in prenatal care [message #22111 is a reply to message #22094] |
Tue, 02 February 2021 09:05  |
Bridgette-DHS
Messages: 3172
Registered: February 2013
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Senior Member |
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Following is a response from DHS Research & Data Analysis Director, Tom Pullum:
I agree that you should be cautious about assuming that the wealth quintile of the household is constant over time. However, looking at earlier DHSs in the same country will not help with this issue. The households and clusters are completely different in successive surveys. Assuming that the household was in the same wealth quintile five years ago (or even earlier) that it is in at the time of the survey may be your best option.
It would be possible to use just the birth histories in the IR file to construct a variable like this: D is the number of child deaths at age<A months during the M months prior to the interview. For example, with A=12 and M=60, this would be the number of infant deaths in the past five years. I would construct D such that it would be a dot, or NA, if the woman did not have any children who had a risk of dying at age<A during the reference period. To calculate this you would loop through the b variables (subscripted with _01, _02,...,_20), focusing mainly on b3 and b7.
This is a non-trivial recode. Unfortunately I just don't have the time to do it--you will have to do it yourself. The main complication is that we don't know the cmc of death, for children who died. We know cmc of birth (b3), and age at death, in months (b7). After 23 months, b7 is in intervals, coded with the midpoint month of a 12-month interval.
I am not sure how this variable would be used in a model. It could be an interesting outcome variable, but you would have to be careful using it to predict something else.
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