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Statistics in Clinical Trials for the Non-Statistician

Discover the crucial role statistics plays in clinical trials and enhance your understanding of clinical trial data and analysis.

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Statistics in Clinical Trials for the Non-Statistician

  • 3 weeks

  • 6 hours per week

  • Digital certificate when eligible

  • Introductory level

Find out more about how to join this course

  • Duration

    3 weeks
  • Weekly study

    6 hours
  • 100% online

    How it works
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    $244.99 for a whole yearLearn more

Gain statistical knowledge and skills to advance clinical research

Whatever your role in clinical research, this online course from the University of Birmingham will build your statistical knowledge and skills directly applicable to clinical trials.

In just three weeks, you’ll gain the confidence to use what you’ve learned to enhance your enjoyment, engagement and participation within a trial team and improve the quality of future trials, better informing your clinical practice.

Summarise data generated in a clinical trial

You’ll begin by learning how to meaningfully summarise the vast amount of data collected in a trial and how to compare health outcomes across patients, to make formal comparisons between different treatments.

Draw meaningful inferences from trial findings

You’ll learn how statistical tests and models can assess whether any observed difference between two treatments is likely to be real or due to chance, and how confidence intervals enable us to draw more appropriate inferences about the magnitude of potential treatment effects.

Ensure precise and accurate results – even when things go wrong

You’ll learn how crucial sample size calculations are to guarantee precise estimates of treatment effect and how we ensure accurate findings when problems such as non-compliance to treatment and missing data occur.

Utilise appraisal skills to interpret published research and improve the reporting of future studies

Finally, you’ll learn how to recognise poor analyses or interpretation of results in published reports of trials, improving your critical appraisal skills and better informing your own future trials.

Syllabus

  • Week 1

    Summarising trial data and estimating treatment effects

    • Introduction to the course

      We start by setting the scene, with a brief reminder of the randomised controlled trial, the gold standard study design to evaluate the effectiveness of interventions in healthcare, and the role of statistics within such studies.

    • Collecting and summarising data

      Clinical trials collect a huge amount of data. During this activity, we will learn about the different types of data commonly collected in trials and how we can best summarise these data to make sense of them.

    • Estimating the effectiveness of an intervention

      Next, we consider ways to measure the impact of different interventions on health outcomes, and estimate how effective one intervention is compared to another.

  • Week 2

    Confidence intervals, hypothesis testing and sample size

    • Confidence intervals

      An estimate of treatment effect comes from a single sample drawn from the population. A different sample would lead to a different estimate. So what range of values could the true treatment effect plausibly take?

    • Hypothesis testing

      We now consider hypothesis testing, used to decide whether the data observed in our trial supports a particular hypothesis. For example, are two interventions equally effective, or is one superior to the other?

    • Transformations and non-parametric data

      A lot of the statistical methods we have covered so far assume that data follows a normal distribution. What can we do when this is not the case?

    • Determining the sample size for a trial

      How do we determine how many participants to recruit to a trial and why does sample size matter?

  • Week 3

    Time-to-event data, missing data/non-compliance, advanced topics

    • Time-to-event data in trials

      Interest often lies in the time taken until a specific event for each participant, such as resolution of symptoms, death, or recurrence of disease. Such data requires alternative statistical methods.

    • Dealing with missing data and non-compliance in trials

      Common problems that affect virtually all clinical trials are missing data and non-compliance with planned interventions. What are the implications of such problems and how are they best dealt with?

    • Statistical analysis plans and publication recommendations

      Statistical analyses need to be planned in advance and reported transparently and accurately. Published guidelines exist for analysis plans, protocol and result papers.

    • Advanced topics

      The course ends with an introduction to subgroup analyses and Bayesian statistical methods, and common problems seen in published trial analyses.

When would you like to start?

Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Identify the key statistical concepts and methods used within clinical trials and other studies conducted in healthcare research
  • Summarise data of different data types
  • Identify appropriate measures of treatment effect
  • Interpret the findings of clinical trials published in the medical literature, including estimates of effect, confidence intervals and P-values
  • Critique published analyses of clinical trials, identifying common problems
  • Report statistical methods and results appropriately and transparently
  • Contribute more confidently to a clinical trial team
  • Explain the crucial role that statistics play in a clinical trial, in its design, conduct, analysis, and reporting

Who is the course for?

This course is ideal for individuals involved in clinical trials, whether in academia or the NHS, as well as those without a background in statistics. This includes aspiring chief investigators, research nurses, trial coordinators, trial managers, data managers, quality assurance team members, trial administrators, and other members of trial teams such as qualitative researchers or health economists.

The course is introductory with no prior knowledge or experience of statistics required.

What software or tools do you need?

Learners need no specific software, hardware or other resources to complete this course.

Who will you learn with?

Sara Brookes

I am the Training & Education Lead for Clinical Trials within the Cancer Research UK Clinical Trials Unit hosted by Birmingham University. I have 30 years experience working within clinical trials.

Who developed the course?

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University of Birmingham

The University of Birmingham is a public research university, consistently listed as a leading UK university and ranked among the top 100 in the world.

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Ways to learn

Choose the best way to learn for you!

Subscribe & save

$244.99 for a whole year

Automatically renews

Develop skills to further your career

  • Access to this course
  • Access to 1,000+ courses
  • Learn at your own pace
  • Discuss your learning in comments
  • Digital certificate when you're eligible

Cancel for free anytime

Buy this course

$54/one-off payment

Fulfill your current learning need

  • Access to this course
  • Learn at your own pace
  • Discuss your learning in comments
  • Printed and digital certificate when you’re eligible

Limited access

Free

Sample the course materials

  • Access expires 25 Feb 2025

Find out more about certificates, Unlimited or buying a course (Upgrades)

Sale price available until 3 March 2025 at 23:59 (UTC). T&Cs apply.

Find out more about certificates, Unlimited or buying a course (Upgrades)

Sale price available until 3 March 2025 at 23:59 (UTC). T&Cs apply.

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