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Re: Data inconsistencies [message #23064 is a reply to message #23063] Wed, 07 July 2021 11:00 Go to previous messageGo to previous message
Bridgette-DHS is currently offline  Bridgette-DHS
Messages: 3054
Registered: February 2013
Senior Member

Following is a response from DHS Research & Data Analysis Director, Tom Pullum:

On the basis of my own experience, I'd say it is very unlikely that you will actually encounter any of these inconsistencies in your analysis. For all practical purposes you can ignore the list. But if you have a table or model that includes a variable with known inconsistencies, you can define and use an alternative variable. For example, add the letter "r" for "recoded" and recode it as a dot (which normally means Not Applicable) for the inconsistent values. It is important not to save "corrected" variables under the original name. I would not use a statistical method to adjust for inconsistencies or to impute "corrected" values. If you change values in any way, it's helpful to state that you have done so. Otherwise, other users cannot match your results.

 
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