- Loss of variability: Replacing missing values with a single value (the median) can reduce data variability, potentially leading to biased results. - Not suitable for all data types: Median imputation is not appropriate for categorical data or for variables with a high percentage of missing values. - Potential bias: While it reduces the impact of outliers, it may still introduce bias if the missing data is not randomly distributed.
