A Visual Tool to Help Develop a Statistical Analysis Plan for Randomized Trials in Palliative Care

Area of Science:

• Biostatistics
• Data Science
• Research Methodology

Background:

• Effective collaboration between researchers and statisticians is crucial for robust study design.
• Developing a statistical analysis plan (SAP) requires clear communication of analytical strategies.

Purpose of the Study:

• To demonstrate how directed acyclic graphs (DAGs) can enhance the conceptualization of statistical tasks.
• To present DAGs as a tool for improving collaboration in SAP development.

Main Methods:

• Conceptualizing statistical analysis planning through the lens of directed acyclic graphs (DAGs).
• Utilizing DAGs to visually represent the statistician's approach to data analysis.

Main Results:

• DAGs provide a clear illustration of a statistician's thought process in designing an SAP.
• The visual nature of DAGs facilitates better understanding and communication during collaborative planning.

Conclusions:

• Directed acyclic graphs (DAGs) serve as an effective tool for enhancing statistical analysis plan development.
• Implementing DAGs can lead to more efficient and productive collaborations between researchers and statisticians.