Reading papers related to the imputation of missing values related to the -omics field, systematically imputation algorithms were less accurate when imputing MNAR compared to imputing MCAR. My intuition is the following: Missing values are classified as MNAR when there is a process behind the generation of the data that influence the missing values. Then to be able to impute those MNAR, it is not enough to find relationships between features, rather, it is more important to know the process which is behind the missing values to impute.
Is my intuition right? am I missing other essential points?