Reproducibility
Definition
Reproducibility refers to the ability to obtain similar results when a study is repeated using the same methods, data, and analytical procedures.
Correct Scientific Usage
Reproducibility is achieved when independent researchers can take the original data and analysis code and generate the same numerical results, figures, and statistical conclusions. It requires transparent reporting of methods, sharing of data and code, and sufficient documentation for others to follow the exact analytical steps.
Common Misunderstandings
Reproducibility is often confused with replication. Reproducibility means re-analyzing existing data produces the same results; replication means collecting new data produces consistent findings. A study can be fully reproducible (the analysis is correct) but fail to replicate (the finding doesn't hold with new data). Reproducibility verifies computational accuracy, not whether conclusions are true.
Why It Matters
Reproducibility allows others to verify that analyses were conducted correctly and results were reported accurately. It catches errors, identifies methodological choices that affect outcomes, and enables others to build on existing work. However, reproducibility alone is insufficient—replication with independent data is needed to determine whether findings represent genuine effects rather than artifacts of a particular sample.
References
- Six factors affecting reproducibility in life science research and how to handle them, Nature Portfolio
- Improving Reproducibility and Replicability, Reproducibility and Replicability in Science