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Reproducibility

Subject librarians can work with individuals, research groups, and departments to advise on many aspects of reproducibility and rigor. If you have any questions reach out to the subject librarian for your area. 

Reproducibility is a core principle of scientific progress. Scientific claims should not gain credence because of the status or authority of their originator but by the replicability of their supporting evidence.

Services for reproducible research

The University Libraries support students and researchers across the University of Minnesota and have many experts and services that can support research reproducibility and rigor across the research lifecycle.

The library has subject librarians for each discipline who can

  • help you find reporting guidelines,
  • help you manage your data and understand data sharing requirements and options, 
  • find repositories for pre-registering studies and analysis plans, and
  • answer more discipline specific questions.  

We are also happy to present in classes and workshops on this topic.

Consult with a subject librarian

Methods

Find and use reporting guidelines

Reporting guidelines provide specific instructions for what you need to report about your methodology so others can evaluate and reproduce your work.

There are reporting guidelines for all type of qualitative and quantitative research. 

Equator Network A comprehensive database of reporting guidelines and links to other resources relevant to research reporting.

Research data management

Data management improves the consistency and rigor of your research data so that when you report your research others can understand and interpret it. 

Manage your data Consult with a data management expert at the Libraries, or request a training session.

Systematic review support

Librarians have extensive experience conducting systematic reviews, and the involvement of librarians has been shown to improve the quality and reproducibility of systematic reviews. 

Systematic reviews and evidence synthesis Evidence synthesis reviews encompass systematic reviews, scoping reviews, meta-analyses, and evidence gap maps. These research methods include a reproducible and transparent methodology.

Reporting and dissemination

Tools for pre-registration

Pre-registering your studies and analysis plans ensures that your study can be found and readers can differentiate exploratory from confirmatory research. 

Clinicaltrials.gov ClinicalTrials.gov is a database of privately and publicly funded clinical studies conducted around the world. Open Science Framework (OSF) OSF is a free and open source project management tool that supports researchers throughout their entire project lifecycle.

Reproducibility

The ability to verify results

Curating and sharing your research data, code, and materials, means others can reproduce your results. 

Data Repository for the University of Minnesota (DRUM) DRUM is a publicly available collection of digital research data generated by U of M researchers, students, and staff. Anyone can search and download the data housed in the repository, instantly or by request.

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Definitions

Reproducibility

The ability of a researcher to duplicate the results of a prior study using the same materials and procedures as were used by the original investigator.

Bollen et al, 2015

In this “replication crisis” era, reproducibility is the only thing that can be effectively guaranteed in a published study. Whether any claimed findings are indeed true or false can only be confirmed via additional studies, but reproducibility can be confirmed immediately.

Broman, et al. 2017

We have also created a resource "Reproducibility Bibliography: Guidelines and Examples" which includes definitions, guidelines, and examples related to reproducibility for their disciplines.

Replicability

The ability of a researcher to duplicate the results of a prior study if the same procedures are followed but new data are collected.

Bollen et al, 2015

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Guidelines

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Other campus resources

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References

Broman, K., Cetinkaya-Rundel, M., Nussbaum, A., Paciorek, C., Peng, R., Turek, D., & Wickham, H. (2017). Recommendations to Funding Agencies for Supporting Reproducible Research. American Statistical Association.

Bollen, K., Cacioppo, J., Kaplan, R., Krosnick, J. A., & Olds, J. L. (2015). Social , Behavioral , and Economic Sciences Perspectives on Robust and Reliable Science. Report of the Subcommittee on Replicability in Science Advisory Committee to the National Science Foundation Directorate for Social, Behavioral, and Economic Sciences.

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