In the case of “Missing not at random” (MNAR). Can non-missing data analysis be used to infer missing data? In the example you gave of the stress level, let's say the stress level is a value from 0 to 10. If the current data indicates, for values from 0 to 7, a normal, or uniform, or any other identifiable distribution, presenting exceptions to this distribution only in the quantities of values from 8 to 10, can we use the inferred distribution to insert the missing data?
In the case of “Missing not at random” (MNAR). Can non-missing data analysis be used to infer missing data? In the example you gave of the stress level, let's say the stress level is a value from 0 to 10. If the current data indicates, for values from 0 to 7, a normal, or uniform, or any other identifiable distribution, presenting exceptions to this distribution only in the quantities of values from 8 to 10, can we use the inferred distribution to insert the missing data?