Handling MNAR requires more sophisticated methods than those used for MCAR or MAR. Some common methods include:
Pattern-Mixture Models: These models divide the data into different patterns based on the missingness and model each pattern separately. Selection Models: These models explicitly model the mechanism causing the missingness. Bayesian Methods: These methods incorporate prior distributions and can be useful when dealing with MNAR data by incorporating expert knowledge about the missingness mechanism.
