| Re: Children ever death and children ever died [message #30427 is a reply to message #30404] |
Wed, 27 November 2024 11:46  |
Janet-DHS
Messages: 893
Registered: April 2022
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Senior Member |
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Following is a response from DHS staff member, Tom Pullum:
Thanks for the thanks!
There is no need to merge the IR and BR files. The BR file has one record for each birth in the woman's birth history. That record includes most of the mother's variables from the IR file, including the summary variables v201-v209. The IR file has one record for each woman (whether or not she ever had any children). It includes all of the b variables with subscripts. For the most recent birth, for example, b4_01 is the sex of the child and b5_01 is the survival status. I believe the question is which of these files do you want to use, NOT how do you merge them.
I'm not sure how you would apply SEM to the data. I suggest something a little different. Your research question could be, for example, "Does having a child death increase the probability of having another birth?" It could be that women (or parents) try to replace a child who has died. The probability could change over time and could depend on the sex of the child who died or the current sex composition. If this is what you are thinking of, please let us know and I can suggest a way to do it.
Another strategy with repeated surveys is to take a cohort perspective. For example, women born in 1980 (Gregorian calendar) will appear in all of the surveys, at different stages of family building. You can re-organize the data into a quasi-longitudinal structure. I do this sometimes when checking whether successive surveys in the same country are consistent with one another.
For SEM there is the crucial limitation that you only have a sequence of independent cross-sections and almost all the variables describe current status. There's not much retrospective information outside of the birth histories. Rather than jumping into a complex analysis, I strongly suggest that you start the analysis with a simple approach, using crosstabs and regressions, and then add complexity to the extent that it is possible and necessary.
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