Handling missing data in longitudinal randomized clinical trials within the framework of targeted learning under MAR and MNAR

Key Points

• Effective handling of missing data positively impacts the analysis of longitudinal trials, enhancing accuracy.
• Adding targeted learning approaches improves the handling of both MAR and MNAR missing data scenarios substantially.
• Randomized clinical trial framework allows for robust insights, especially in the context of longitudinal data loss.
• This methodology supports future trials by emphasizing the importance of addressing data completeness.