Home » Countries » India » Help with fertility preference variables v627, v628 and v629 and v613
Help with fertility preference variables v627, v628 and v629 and v613 [message #6733] |
Mon, 06 July 2015 08:49 |
Kathryn Kershaw
Messages: 3 Registered: July 2015 Location: London, UK
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Hi,
Could someone please help me with the following: v627, ideal number of boys and v628, ideal number of girls and v629, ideal number of either sex have an "Other" category, where the respondent has given a non-numeric answer for v613, her ideal number of children. Can I categorise this as having no preference for either the number of children or the sex of her children? Or do I need to treat these values as missing?
Also, as a follow up to that question, if someone has indicated that she would like to have 16 children in variable v613, 8 girls and 8 boys, presumably I ought to include that in my analysis and not treat it as an outlier, is this correct?
Thanks and kind regards
Kathryn
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Re: Help with fertility preference variables v627, v628 and v629 and v613 [message #6737 is a reply to message #6733] |
Mon, 06 July 2015 18:34 |
Bridgette-DHS
Messages: 3199 Registered: February 2013
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Senior Member |
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Following is a response from Senior DHS Stata Specialist, Tom Pullum:
Decisions such as this are really judgment calls. That is, there is not a single "correct" way to handle them.
In a quantitative analysis of the responses, a non-numeric response must be coded "missing" or in some other way be excluded from calculations such as a mean. However, you do need to say something about the prevalence of such responses. You could report the overall percentage of responses that are non-numeric and the percentage in major categories such as place of residence, wealth quintile, etc., and then exclude them from calculations.
If you are reporting, say, the percentages who would prefer a boy or would prefer a girl, then the percentage with no preference is important and could be a separate category. You could consolidate the non-numeric responses with that category. I suggest that you look at an old DHS report by Fred Arnold ( https://www.dhsprogram.com/publications/publication-CS23-Com parative-Reports.cfm) for some suggestions.
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