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A Framework for Open and Reproducible Research Training

FORRT is centred around a framework comprising six clusters of open and reproducible research practices. Each cluster has six sub-clusters.

Cluster 1



Cluster 1: Reproducibility crisis and Credibility Revolution


Summary: Attainment of a grounding in the motivations and theoretical underpinnings of reproducible and open research. Integration with field specific content (i.e., or grounded in the history of replicability);

  • Replication crisis and credibility revolution
  • Exploratory and confirmatory analyses
  • Questionable research practices (their ‘theory’) and prevalence
  • Proposed improvement science initiatives on statistics, measurement, teaching, data sharing, code sharing, pre-registration, replication.
  • Ongoing debates, (e.g. incentives for and against open science).
  • Ethical considerations for improved practices.

Although not exhaustive, these concepts provide a broad coverage of this cluster.

Cluster 2



Cluster 2: Conceptual and Statistical Knowledge


Summary: Enacting this principle indicates that students attain a grounding in fundamental statistics, measurement, and its implications.

  • The logic of null hypothesis testing, p-values, Type I and II errors (and when and why they might happen).
  • Limitations and benefits of NHST, Bayesian and Likelihood approaches.
  • Effect sizes, Statistical power, Confidence Intervals.
  • Research Design, Sample Methods, and its implications for inferences.
  • Questionable research (QRPs) & measurement practices (QMPs).
  • Understand the relationship between all of the above.

Although not exhaustive, these concepts provide a broad coverage of this cluster.

Cluster 3



Cluster 3: Reproducible analyses


Summary: Reproducible analyses allow the checking of analytic pipelines and facilitate error correction. Enacting this principle requires students to move towards transparent and scripted analysis practices.

  • Strengths of reproducible pipelines
  • Scripted analyses compared with GUI
  • Data wrangling
  • Programming reproducible data analyses
  • Open source and free softwares
  • Tools to check yourself and others; statcheck, GRIM, and SPRITE

Although not exhaustive, these concepts provide a broad coverage of this cluster.

Cluster 4



Cluster 4: Open data and materials


Summary: Enacting this principle indicates that students have attained a grounding in open data and materials in both; using and sharing.

  • Knowledge of traditional publication models. Open access publishing, preprints
  • Reasons to share; for science, and for one’s own practices
  • Repositories; e.g. OSF, FigShare, GitHub
  • Accessing/sharing others data, code, and materials
  • Ethical considerations
  • Examples and consequences of accessing un/open data

Although not exhaustive, these concepts provide a broad coverage of this cluster.

Cluster 5



Cluster 5: Preregistration


Summary: Preregistration entails laying out a complete methodology and analysis before a study has been undertaken. This facilitates transparency and removes several potential QRPs.

  • Purpose of preregistration - distinguishing exploratory and confirmatory analyses, transparency measures
  • Preregistration and registered reports - strengths and differences
  • When can you preregister? Can you preregister secondary data?
  • Writing a preregistration
  • Comparing a preregistration to a final study manuscript
  • Conducting a preregistered study

Although not exhaustive, these concepts provide a broad coverage of this cluster.

Cluster 6



Cluster 6: Replication research


Summary: Replication research takes a variety of forms, each with a different purpose and contribution. Reproducible science requires replication research.

  • Purposes of replication attempts - what is a ‘failed’ replication?
  • Large scale replication attempts
  • Distinguishing conceptual and direct replications
  • Conducting replication studies; challenges, limitations, and comparisons with the original study
  • Registered Replication Reports
  • The politics of replicating famous studies

Although not exhaustive, these concepts provide a broad coverage of this cluster.