Dear all
I have a question concerning the inclusion of (auxiliary) variables into
the missing data procedure. I understand that a rather "inclusive"
strategy can increase efficiency and reduced bias.
Now, I also have the feeling that the inclusion of a certain (auxiliary)
variable can have an additional cost that depends on the degree of
missingness of this (auxiliary) variable itself. If the latter is "too
high", couldn't this result in a higher disadvantage of including this
variable relative to the advantage (increase in efficiency and/or
reduced bias) that the inclusion of the variable could have? If yes,
does there exist a measure/rule of thumb to evaluate and judge on this
trade off?
Thank you for your efforts.
Philippe