Reporting guidelines

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This page is under development. Changes should be expected.

Reporting guidelines help improve readers understanding of a project (design, conduct, analysis, and interpretation) and enable them to better assess the validity of the projects results.

Because different project types require different things to be reports, there are many guidelines for reporting different types of projects.

Randomised trials

• CONSORT - guidelines for publishing RCTs
  • Checklist
  • Statement
  • Flow diagram
  • DISCOURAGES USE OF P-VALUES/CONFIDENCE INTERVALS/STANDARD ERRORS IN DESCRIPTIVE TABLES (e.g. Table 1) - POSSIBLY USEFUL TO REFUTE REVIEWER REQUESTS FOR THEM (see also the Datamethods reference collection on “common myths”)
  • Extension for adaptive designs
    • (checklist in the supplementary materials)

Observational studies

• STROBE - guidelines for reporting of observational studies
  • STROBE website
  • STROBE checklists
  • The STROBE statement itself has been published in many journals (see here)

Systematic reviews and meta analyses

• PRISMA - guidelines for transparent reporting of systematic reviews
  • Homepage
  • Checklist
  • Extensions to the original statement
  • Link registration details page where registrations are actually made on PROSPERO
  • Note that systematic reviews/metaanalyses are sometimes/often rejected by journals for not having been registered

Predictive models

• TRIPOD - guidelines for reporting of predictive/prognostic models (validation or derivation)
  • Moons et al 2015
  • Moons et al 2012
  • TRIPOD checklists
  • Alternate site for derivation/validation checklist

Not a reporting guideline per se, but a method of assessing risk of bias and applicability of prediction model studies - PROBAST

• PROBAST paper
• further explanations and elaboration of PROBAST
• useful along side TRIPOD perhaps?
• use of PROBAST to assess ML models in ocology. Long story short, most models are high risk > 123 (81%, 95% CI: 73.8 to 86.4) developed models and 19 (51%, 95% CI: 35.1 to 67.3) validated models were at high risk of bias due to their analysis, mostly due to shortcomings in the analysis including insufficient sample size and split-sample internal validation

Others

• Latent trajectory studies (GRoLTS)
  • The GRoLTS-Checklist: Guidelines for Reporting on Latent Trajectory Studies

Find additional guidelines

• The new open-access database LIGHTS - Library of Guidance for Health Scientists - is a very usefull tool to support the search for methods guidance.

• The EQUATOR Network also has links to many other guidelines (SPIRIT, CARE, AGREE, …)

• The COMET Initiative has a searchable list of standardised outcome sets for diseases, conditions etc.