How to deal high multicollinearity during multiple imputation
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8 weeks ago
Phylicia ▴ 10

Hi, I conducted a multiple imputation based on the tutorial of Virginia University. https://data.library.virginia.edu/getting-started-with-multiple-imputation-in-r/

However, the error report is:

imp2 <- mice(merge2, maxit = 5, 
             predictorMatrix = predM, 
            method = meth, print=TRUE)

Error in edit.setup(data, setup, ...) : 
  `mice` detected constant and/or collinear variables. No predictors were left after their removal.

When I establish print=TRUE,it does not show when the algorithm stops because of multicollinearity. How can I do trouble shoot?

Thank you very much!

imputation high multicolinearity multiple • 143 views
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