Missing data can be addressed through several methods:
- Imputation: Estimating and filling in missing values using statistical techniques. - Sensitivity Analysis: Assessing how different methods of handling missing data affect the study results. - Complete Case Analysis: Analyzing only the cases with complete data, though this can introduce bias if the missingness is not random.
