Designing and Analyzing Clinical Trials in R

In this course you will gain an overview clinical trial designs, determine the numbers of patients needed and conduct statistical analyses.
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4 Hours15 Videos48 Exercises3,200 Learners
4000 XP

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Course Description

Clinical trials are scientific experiments that are conducted to assess whether treatments are effective and safe. They are used by a variety of organizations, including pharmaceutical companies for drug development. Biostatisticians play a key role in ensuring the success of a clinical trial. In this course you will gain an overview of the important principles and a practical introduction to commonly used statistical analyses. This course would be valuable for data analysts, medical students, clinicians, medical researchers and others interested in learning about the design and analysis of clinical trials.

  1. 1

    Principles

    Free
    In this chapter you will be introduced to the important principles of clinical trials.
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  2. 2

    Trial Designs

    In this chapter you will be introduced to randomization methods and different types of trial designs.
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  3. 3

    Sample Size and Power

    By the end of this chapter you will be able to calculate the numbers of patients needed for a clinical trial under a range of scenarios.
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  4. 4

    Statistical Analysis

    In this chapter we will explore additional statistical techniques that are commonly used to analyze data from clinical trials.
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Datasets
Acupuncture datasetFact datasetPK dataset
Collaborators
David CamposRichie CottonShon Inouye
Tamuno Alfred Headshot

Tamuno Alfred

PhD. Biostatistician
Tamuno Alfred is a biostatistician with experience in the pharmaceutical industry and in academia. She has worked on several clinical trials and epidemiological studies. Tamuno has an MSc in Medical Statistics and a PhD in Genetic Epidemiology.
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