Timeline for Different categories of missings
Current License: CC BY-SA 4.0
5 events
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| Feb 4, 2019 at 9:19 | comment | added | Kondybas | @user3120868 Can you explain why the duplication is required? Why you can't hold the single reference table for all the kinds and categories piled together? | |
| Feb 3, 2019 at 17:49 | comment | added | user3120868 | I can see how this approach would work but I was hoping that there exists a more elegant solution. This effectively requires duplicating every table (for which I want to capture different categories of missingness). In my original question, I alluded to this potential solution as "Other workarounds include having a parallel table that includes a categorical variable for each continuous variable, where the categorical variable indicates missingness and category of missingness." This solution also requires more code (and opportunities for mistakes) when reading in the data (undesirable). | |
| Feb 1, 2019 at 19:50 | comment | added | Kondybas |
The table of two fields id and the_reason_to_be_null for reference and additional column nullity_reason with FK to the reference table aside the income column. nullity_reason equal to NULL means income IS NOT NULL and all the other values, listed in the reference table, describes the variety of reasons why the income can become NULL. You can add as many reasons to the reference table as you need and extend it in any desirable way.
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| Feb 1, 2019 at 18:08 | comment | added | user3120868 | " All the other subcategories can be implemented as reference table of arbitrary numbers of states." I'm puzzled over how you would implement this. Suppose I have a table that describes some continuous attribute (say, income). Currently, some values are Null. Other values are impossible and I want to code them as Null. But I want to retain information on whether the value was Null when the data was received or Null because we recoded it. How would a reference table allow us to accomplish that? | |
| Feb 1, 2019 at 15:06 | history | answered | Kondybas | CC BY-SA 4.0 |