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Pre-registration of mathematical models
1Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA.
Mathematical Biosciences
|January 29, 2022
Summary
Pre-registration enhances scientific trust by making research plans transparent. This practice, though established, is newly explored for mathematical modeling to improve reproducibility.
Area of Science:
- Scientific methodology
- Mathematical modeling
- Research integrity
Background:
- Pre-registration involves depositing a research protocol before study commencement.
- It enhances trust by making deviations from the original plan transparent.
- While common in some fields, its application to mathematical modeling is less explored.
Purpose of the Study:
- To discuss the feasibility and implications of pre-registration for mathematical modeling studies.
- To explore how pre-registration can improve trust and reproducibility in modeling research.
- To examine the advantages, disadvantages, and realistic goals of pre-registering mathematical models.
Main Methods:
- Discussion and commentary on the concept of pre-registration.
- Analysis of its applicability to various mathematical modeling activities.
- Review of potential benefits and challenges in implementing pre-registration for models.
Main Results:
- Pre-registration can enhance trust in model performance, especially for forecasting tasks.
- Feasibility depends on the modeling type and ability to pre-specify processes and outcomes.
- It contributes to improved documentation, transparency, and sharing in research.
Conclusions:
- Pre-registration offers a valuable tool for increasing the reliability of mathematical modeling research.
- Careful consideration of modeling type and outcome measurability is crucial for successful implementation.
- Adopting pre-registration aligns with broader efforts to enhance research reproducibility and integrity.
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