Normally, I exclude a covariate out of the regression equation if there are many missing observations, let's say it is one-fifth less observation compared to other variables' observations in general (saying 80,000 compared to 100,000).

But now, when reflecting back, I am wondering if there is any reference or explanation for excluding action like that (excluding a covariate having many missing observation)? I think it may relate to the within-sample standard variation and explanation power due to the sample shrinking but I am not sure about that.



Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Browse other questions tagged or ask your own question.