Hi all, I am (seemingly) having some trouble with my imputation model. I am trying to impute values for missing data for variables related to cancer and demographics such as stage, grade, receptor status, and deprivation.

I am using multiple imputation with chained equations, and am correctly specifying the model for each imputed variable as far as I am aware. All the separate models converge, but when I test the imputed values vs observed values after imputing, I am getting some wild differences between the two. I know there is no test to ascertain whether this is a problem, but the differences between the observed and imputed values are concerning me.

Can anyone point me in a sensible direction so I can go about correcting my imputation model?

Many thanks.