I am working with a small sample (n=60) but some of the variables have random missingness while others have non-random missingness.
My questions are:
- Can I use multiple imputations to handle both random and non-random missingness? If not, how should I handle the non-random missingness?
- Can I use multiple imputations in my data at all given my very small size? I have about ~15% missing data.
Any advice or R-code demonstration are greatly appreciated.