| Re: gender matching interviewer / participant in Zimbabwe & Burundi [message #23559 is a reply to message #23555] |
Wed, 06 October 2021 23:04   |
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Bridgette, Tom, and Trevor
Thanks again! Deeply appreciate that you folks go above and beyond to make this data accessible and usable for people like me. You all are great!
I actually didn't have issues with Burundi IR, just the MR. I think there's still an issue with interviewer 2104 as a female interviewing males. I could probably check to determine whether that ID shows up in the IR.
In terms of analysis - the gender itself shouldn't matter much - as it seems as though I can safely assume that I've been merging the same way you would and that in practice, all datasets with the FW data available gender matched interviewers / participants. Other variables, like age, education, etc. do matter a bit. From a combination of Tom's and Trevor's response... sounds like I should:
- Recode enumerator 920 in ZW7 MR from 920 to 903
- Keep interviewer 803 (assuming that the FW data, except for interviewer sex is probably correct)
- Drop the rest (primarily only meaningful for 201 and 207) as it doesn't sound like it's very safe to assume that the FW data is for the people who did the interviews.
No worries at all about STATA, I appreciate the opportunity to dust off the STATA license on my computer. I really should be better about maintaining that skillset. I did notice that DHS program has started to publish code to reproduce indicators on github, including in R. Very cool! I'm not sure if you take pull requests from the public - but if you do, would be happy to submit some pull requests following the conventions you've got there for some of the sections that haven't been published yet.
Jeffrey W. Rozelle
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