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Nature Research Academies – Clinical Research Methodology
Nature Research Academies – Clinical Research Methodology

Nature Research Academies – Clinical Research Methodology

Available from Nature Research Academies: workshops in Clinical Research Methodology. Nature Research Academies is a series of training workshops for researchers, developed by Nature Research.

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Academy in Clinical Research Methodology

Understanding the elements of robust research methodology is essential to any researcher in order to avoid problems such as research waste, manuscript rejections and/or long peer-review process.

Nature Research Academies has developed this 1-day interactive workshop in ‘Clinical Research Methodology’ to provide clinicians with tools and strategies to write solid research protocols and avoid common problems in data collection and analysis.

  • 1-day workshops
  • Available to institutions globally, to host on-site
  • For up to 50 clinical researchers

Feedback from participants

“It is very useful for me to understand publication strategies and how to design and write clinical research papers.”

“This is a wonderful workshop! Dr. Robens used a lot of examples and activities to help us understand, so I feel I learned many useful skills.”

Academy content

  • Planning a clinical study
    • Identifying a strong research problem
    • Assessing the quality of your research question
    • Deciding the right outcomes to measure
  • Appropriately sampling your participants
    • Performing a power calculation
    • Deciding inclusion and exclusion criteria for participant selection
    • Recruitment methods that avoid sampling bias
  • Choosing the right study design
    • Pyramid of clinical relevance
    • Strengths and weaknesses of study designs
    • Designing a randomized controlled trial
    • Choosing the right control
  • Avoiding common biases
    • Most common biases in clinical studies
    • Strategies to avoid those biases
  • Properly collecting and analyzing data
    • Managing data
    • Handling missing data
    • Performing multiple comparisons
    • Clinical vs. statistical relevance

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