Handling MNAR requires specialized statistical techniques and careful study design:
Sensitivity Analysis: Conducting analyses to understand how different assumptions about the missing data could impact the results. Multiple Imputation: Using advanced algorithms to estimate the missing values based on observed data and plausible assumptions. Pattern-mixture Models: Developing models that incorporate various patterns of missingness to adjust the results accordingly.
