Choosing the best method for handling missing data depends on several factors:
Extent of Missing Data: If a large proportion of the data is missing, more sophisticated methods like multiple imputation may be needed. Pattern of Missing Data: Understanding whether data is MCAR, MAR, or NMAR is crucial in deciding the appropriate method. Study Design and Objectives: The choice of method should align with the study's design and research objectives. Available Resources: Some methods require more computational resources and expertise.
