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Understanding and ensuring Reproducibility in your research

Reproducibility is pivotal to research. Researchers from various disciplines must be aware of valid studies to build on, sifting away unreliable methods and data, or worse still, false leads. When the findings of a study guide policies, particularly those impinging on issues such as human health (as has been witnessed during the COVID-19 pandemic), the reliability of the study becomes even more significant. Therefore, researchers corroborate new discoveries by repeating the study that produced them.

To better understand and ensure reproducibility, though, let’s begin by comparing it with two related terms.

Reproducibility vs. Repeatability and Replicability

Repeatability, replicability and reproducibility comprise the three Rs in research. While all three underpin the reliability of academic output, the overlap among these terms can be confusing. Let’s examine the differences.

Term Description Significance
Repeatability When the same researchers obtain the same result by using the same methods under the same conditions in the same location, multiple times, it means the study is repeatable. Repeatability measures precision under repeated conditions.
Replicability When a different set of researchers arrives at the same results using the same methods under the same conditions in the same or a different location as those of the original authors, the study is said to be replicable. The result is not due to chance or an experimental artefact.

Reproducibility refers to a different group of researchers arriving at the same results using their own data and methods.

Thus, reproducibility answers the following questions:

  • Is there sufficient transparency and clarity on the data and analysis to enable verification of the results?
  • Do the data and analysis support the result?

Importance of reproducibility in research

Editors, reviewers and other researchers evaluate papers for the reproducibility aspect. This has become common practice ever since numerous studies exposed a “reproducibility crisis”. Reproducibility provides confidence that independent researchers have validated an observation/finding. 

When a study cannot be reproduced, it could point to any of the following:

  • Flawed research: This suggests errors arising from carelessness or ethical misconduct (including, for example, deliberate fudging of data and fake data).
  • Unclear reporting
  • Non-disclosure of critical experimental information

Journal requirements for reproducibility

  • Accordingly, academic journals require that the Materials and Methods section include sufficient technical information to allow the experiments to be repeated.
  • Many journals also ask for data availability statements providing details and links to datasets analysed or generated. 

How to ensure reproducibility in your research

a. Be ethical

  • Pre-register your study (i.e. submit your hypotheses and plans for data analysis to a repository before performing experiments).
  • Be as objective as possible when reporting, analysing and interpreting your findings
  • Don’t try to manipulate or hide negative findings

b. Ensure rigour

  • Choose the best study design, keeping in mind statistical power and appropriate effect size.
  • Minimise errors and avoid sloppiness.
  • Use appropriate analysis and reporting. 

c. Uphold transparency

  • Clearly describe the study design, materials used, detailed step-by-step methods, code (if any) and details of data collection and analysis, in your paper. 
  • Share voluminous data as supplementary material or hyperlinks to large databases.
  • Always maintain a record of all your raw data for posterity. 


Reproducibility is a crucial aspect for researchers to be able to build on earlier work and further scientific progress. As a responsible researcher, you should be confident that you or anybody can reproduce your work based on the details and data you have provided.


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