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  • Multiple Imputation for Index Variable

    Hello,

    I have large survey data in which I am constructing indices using some of the variables.

    When conducting multiple imputations, would I:
    1. Generate the indices prior to mi. Then register both the components with -mi register imputed- and the indices under -mi passive-. Then only include the index variables during regression?
    2. First register the components with -mi register imputed- and then construct the index after?

    I have tried the Stata documentation/online resources but I find myself still lost on the topic.

    Any help is greatly appreciated! Let me know if any other information is required or if clarification is needed on how I worded my question.

  • #2
    this is one of the major controversies remaining in MI - the first is often referred to as just-another-variable (JAV) and the second as "passive" - there are good points and bad points about each (e.g., is you use #1, it is almost certainly the case that the imputed index will not be what would get if you followed #2 - in fact, they can be quite inconsistent (and some people very much dislike that) - but #2 can lead to "uncongeniality" which, in some cases can be disastrouss - there are studies, using simulation, that come down for #1 and other studies, using other simulations, that come drown for #2; further, there is a more recent line of lit that dismisses both and says to use "factored regressions" (not available in Stata); since your question was very general, my answer is also

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    • #3
      Originally posted by Rich Goldstein View Post
      this is one of the major controversies remaining in MI - the first is often referred to as just-another-variable (JAV) and the second as "passive" - there are good points and bad points about each (e.g., is you use #1, it is almost certainly the case that the imputed index will not be what would get if you followed #2 - in fact, they can be quite inconsistent (and some people very much dislike that) - but #2 can lead to "uncongeniality" which, in some cases can be disastrouss - there are studies, using simulation, that come down for #1 and other studies, using other simulations, that come drown for #2; further, there is a more recent line of lit that dismisses both and says to use "factored regressions" (not available in Stata); since your question was very general, my answer is also
      To clarify if I choose the JAV approach, during -mi impute chained- I would impute both the components and the index itself? Even though the components will not be used again?

      Ex.
      Code:
       
      mi register imputed component1 component2 component3 index depvar
      mi impute chained (logit) component1 component2 component3 depvar (ologit) index
      mi estimate logit depvar i.index
      Or would it be like:
      Code:
       
      mi register imputed component1 component2 component3 depvar
      mi register passive index
      mi impute chained (logit) component1 component2 component3 depvar = index
      mi estimate logit depvar i.index

      Comment


      • #4
        yes, if using the JAV approach, you "would impute both the components and the index itself"

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