# MAR Assumption missing data

I want to do predictions of missing data MAR. I do the simulations by generating normal data with 1 y and some x. after that I remove the data: Proportion of missing value from 5%, 10% to 50%. I use imputation mice. I would to ask, how much imputation should I do for each of the missing data proportions. I have not found literature about it. I just get the MCAR, the amount of imputation is as much as a lot of missing data.