ADVANCEing CLINICAL TRIALS: a statistical guIDe

Accessible clinical trial statistics: concepts, methods with real-world examples

Available September 2026

Clinical research and clinical trials of high quality require a strong multidisciplinary team of experts ranging from physicians and nurses to statisticians and epidemiologists, from trial managers to data managers, who must communicate together effectively. ADVANCE-ID has embraced multi-disciplinary collaboration to improve knowledge and understanding among peer trialists. In doing so, efforts are combined to achieve research breakthroughs, enabling the implementation of good health care practice to benefit patients.

There are a multitude of different clinical trial designs, each of which requires specific statistical planning and analyses. This seminar series will be a practical introduction to several statistical concepts that are the foundation of clinical trial design to help non-statisticians improve their clinical trial literacy. Leading experts in the field describe advantages and disadvantages of different clinical trial designs, effect measures and statistical philosophy, along with their impact on sample size calculations and their statistical analysis. It will be a free modular series, which you can follow at your own convenience.

Speakers

Prof Sarah Walker (London, UK)

Dr Sue Lee (Bangkok, Thailand)

Dr Sean Ong (Toronto, Canada)

Prof Ronald Geskus (Ho Chi Minh City, Vietnam)

Prof Tom Snelling (Sydney, Australia)

Dr Pavel Mozgunov (Cambridge, UK)

Dr Rob Mahar (Melbourne, Australia)

Dr Angela Huttner (Geneva, Switzerland)

Dr Mo Yin (Singapore)

Format

Each seminar will include an accessible introduction to the statistical concept using examples from real clinical trials.

Topic 1: Cross-Overs, Factorials & Parallel Trial Plot Twists
Topic 2: The Art of Randomisation
Topic 3: Measuring What Matters: Outcome Types in Clinical Trials
Topic 4: The Trial Objectives Trilogy
Topic 5: Beyond the p-value
Topic 6: Trials that Learn and Adapt
Topic 7: Trial and Error
Topic 8: Reporting Right and Evaluating Smart
Topic 9: From Benchmark to Bedside

Target Audience

Early-Mid career investigators with an interest, or experience, in clinical research or clinical trials with limited or no statistical knowledge.

Learning Outcomes

After following this seminar series participants should be able to:

1. Describe commonly used clinical trial designs, objectives and outcome measures and explain the most appropriate settings for their use.
2. Describe and explain the impact of trial design, objectives and outcome measures on the statistical analysis of clinical trials.
3. Describe how to appropriately interpret and utilise findings from published clinical trials.

Videos

Topic 1: Cross-Overs, Factorials & Parallel Trial Plot Twists

This lecture explains the rationale behind and key features of three different types of design for randomised controlled trials (parallel group, cross-over and factorial), their advantages and disadvantages, and methods of statistical analysis.

Click here to download the slides for this presentation.

Topic 2: The Art of Randomisation

Randomized trials are widely considered to provide the highest level of evidence for guiding patient management and for informing health policy. This presentation is designed to guide you through the statistical principles of randomization in clinical trials. By the end of this session, you should be able to describe common randomisation processes, weigh their pros and cons, match different randomization processes to the most appropriate settings, and understand the impact of different randomization processes on analysis.

Click here to download the slides for this presentation.

Topic 3: Measuring What Matters: Outcome Types in Clinical Trials

Outcome selection is a key design choice in clinical trials as it affects how you conduct, analyse, and report a trial, as well as how trial results are interpreted and applied. In this seminar, we explain the features and trade-offs associated with different outcome types, and outline the considerations an investigator should think about when selecting a clinical trial outcome.

Click here to download the slides for this presentation.

Topic 4: The Trial Objective Trilogy

This topic explains three different types of study questions when comparing the efficacy of a new treatment or intervention with an existing one: is the new treatment better, not considerably worse or equivalent. We explain how the type of study question determines the formulation of the null hypothesis and why conclusions can depend on the trial design.

Click here to download the slides for this presentation.

Topic 5: Beyond the p-value

In this seminar, we discuss the misuse of p-values in clinical trial research - particularly when p is less than 0.05 is used as a criterion for casting a verdict on whether a treatment is effective or not. A p-value, by itself, is rarely a sound criterion for judging a treatment. If the goal of a clinical trial is to inform decision-making, we first need to understand how decisions should reflect our beliefs about the potential consequences of our actions, and how we value those consequences.

Click here to download the slides for this presentation.

Topic 6: Trials that Learn and Adapt

In this lecture, you will learn about adaptive clinical trials. We will introduce what an adaptive trial is and what adaptive designs can and cannot do. We will go through several types of adaptations and go through several examples of real trials that faced certain challenges and used these adaptive designs to overcome them.

Click here to download the slides for this presentation.

Topic 7: Trial and Error

This seminar describes the key factors that determine sample size in clinical trials, including the additional factors introduced by adaptive features such as interim analyses. Using a worked example, it demonstrates how simulation can be used to evaluate operating characteristics including power, type I error, early stopping probabilities and expected sample size, and why the number of simulations matters.

Click here to download the slides for this presentation.

Topic 8:  Reporting Right, Evaluating Smart

This presentation introduces students to two guides for reporting trials and assessing the certainty of evidence from studies, respectively. These are the CONSORT guideline for reporting randomized clinical trials, and the GRADE framework for evaluating the certainty of evidence stemming from trials and other studies. At the end of the course, students should be familiar with the CONSORT checklist and its key requirements, and they should understand the four-step GRADE procedure for evaluating the certainty of evidence produced by various studies.  

Click here to download the slides for this presentation.

Topic 9: From Benchmark to Bedside

This session explores how to design clinical trials not just to generate evidence, but to change clinical practice and improve patient care. Designing for uptake means studying representative patients, pragmatic interventions and meaningful outcomes, while collecting qualitative, implementation and health-economic data to understand how evidence can work in the real world. Ultimately, impactful trials engage patients, clinicians, policymakers and other stakeholders throughout the research lifecycle, building equitable and sustainable trial ecosystems that turn evidence into action.

Click here to download the slides for this presentation.

To help improve our future activities, please share your experience with this seminar series with us?