Home » Data » General Data Questions » Operationalization v476
| Re: Operationalization v476 [message #10704 is a reply to message #10700] |
Thu, 01 September 2016 11:35  |
Bridgette-DHS
Messages: 3154
Registered: February 2013
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Senior Member |
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Following is a response from Senior DHS Stata Specialist, Tom Pullum:
First, the code "." means "Not Applicable (NA)" and of course should be omitted from any denominators.
Second, code 9 is not a "valid" response for v476, but it occurs occasionally for many variables for which it is not a valid response, and usually means something like "not stated." and I would agree with you that most analysts would want to omit code 9 and treat it the same as NA. However, for DHS tabulations, it is normal to retain the invalid "9" or "99", etc., in the denominator. I have made my opinion known around here, and lost, but it really doesn't bother me because the number of "9"s is always low.
Third, code 8 or other responses that mean "don't know" or "undecided", or "depends", especially for an attitude question, in my opinion should NOT be removed from the denominator. If you remove those cases, then the balance between "No" and "Yes" can be misleading. But if you keep the "don't know" cases, what do you do with them?
One possibility would be to list them explicitly as a third category. This would be my preference. However, that would cause problems if you wanted to do a logit regression, say. Another possibility would be to divide them evenly between the 0 and 1 categories, but that is a completely ignorant, know-nothing way to divide them. Another possibility would be to divide them between 0 and 1 in proportion to the observed balance between 0 and 1, but that would be equivalent to removing them entirely, i.e. assigning them to NA.
The prevailing practice with DHS would basically be to group the "don't know" cases with the "no" cases. A good example of this is with hiv03, or HIV status, in the AR files. In some surveys you will find a small number of cases in which the HIV blood test was ambiguous or inconclusive. Those cases are not removed, but are classified with the "HIV negative" cases. At one time I disagreed with this practice, but now I'm more accepting of it, because there is an implicit null hypothesis that the person is HIV negative, and if the test result is ambiguous, then it makes more sense to say that it is consistent with the null hypothesis than to ignore it completely. For the question in your example, I think the same reasoning would apply: you should only count a person as a "yes" if they SAY "yes". If they don't say "yes", then count them as a "no" even if they don't quite say "no".
Fortunately, when you do a re-analysis of the data, you have access to the data files and you are free to re-interpret as you wish!
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