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A template for the authoring of statistical analysis plans
Gary Stevens1, Shawn Dolley2, Robin Mogg3
1DynaStat Consulting, Inc., 119 Fairway Court, Bastrop, TX, 78602, USA.
Contemporary Clinical Trials Communications
|June 30, 2023
Summary
Completing a statistical analysis plan (SAP) early in clinical research design optimizes sample size, identifies bias, and improves rigor. This ensures robust study protocols and prevents p-hacking for reliable trial outcomes.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Research Methodology
Background:
- Principal investigators often lack access to biostatisticians or biostatistical training.
- There's frequently no requirement for a timely statistical analysis plan (SAP).
- Early SAP completion is crucial for identifying design flaws and improving protocols.
Purpose of the Study:
- To present a comprehensive protocol template for clinical research design.
- To offer best practice methods for statistical analysis plan (SAP) development.
- To guide statisticians of all levels in creating robust SAPs.
Main Methods:
- Compilation of best practice methods from biostatistical practitioners.
- Inclusion of detailed definitions and diverse examples for SAP sections.
- Development of an ordered corpus of SAP sections.
Main Results:
- Early SAP completion identifies design or implementation weak points.
- SAPs improve protocols, reduce p-hacking, and enable peer review.
- Simultaneous SAP and protocol completion optimizes sample size and rigor.
Conclusions:
- A well-structured SAP is essential for rigorous clinical trial design.
- The presented template facilitates the creation of effective SAPs for statisticians.
- Early and comprehensive SAP development enhances research integrity and outcomes.
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