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A Practical Guide to Randomization in Clinical Trials

About the webinar

Randomization is a central tenet in the design of clinical trials as it allows trialists to ensure their trial generates valid estimates of the effect of their treatment.

However, randomization can take on different forms depending on the practical constraints in a given trial and this can have significant implications on the analysis strategy and the expected power of a trial. 

In this webinar, we discussed why randomization is central to good trial design, how different randomization strategies can affect the statistical methods and power and how appropriate randomization lists can be generated for your trial.

A Practical Guide to Randomization in Clinical Trials

Why it Matters, How it Affects Power and How to Generate a Randomization Lists

A Practical Guide to Randomization in Clinical Trials_Watch Now

In this free webinar you will learn about:

  • What is Randomization & It’s Importance

  • Common Randomization Strategies in Clinical Trials

  • Effect of Randomization of Methods and Power
  • Randomization Lists and Available Algorithms

More about the webinar

A pivotal component for clinical trials is randomization i.e. the random assignment of patients to receive either the experimental treatment(s) or controls.

Without randomization, it can be difficult to ensure statistical comparability for the treatment and thus generate valid statistical estimates. Blinded randomization also prevents operational bias due to trialists’ expectations influencing treatment assignment.

However, randomization can take on different forms depending on the constraints present in a trial or preferred group characteristics of stakeholders.

For example, some larger interventions such as vaccines may require randomization on the level of region or hospital rather than per-subject. This “cluster randomization” has significant effects on the analysis strategy and resulting expected power for a given total sample size.

Therefore it is vital that the randomization strategy is considered carefully and integrated into the study design.

Once a randomization strategy is developed there is still the practical issue of implementation. A common issue is how to generate a randomization schedule that ensures statistical validity and blinding while maintaining certain preferred outcomes e.g. avoiding gender imbalance across groups, accounting for centers.

Randomization list algorithms such as block randomization are a key strategy to creating lists that can be used to generate appropriate group assignments over time.

Watch this free webinar, as we discuss what randomization is and why it is important, some common types of randomization in clinical trials and their effect on analysis methods and power and how randomization list algorithms can be used to randomize subjects while taking account of issues such as centers or covariate imbalances.

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the complete recording of this webinar

Duration: 60 minutes

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EXAMPLE FILES
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Download and explore the data yourself. Data files include:

  • Block Randomization with Stratification Example.nqrl  
  • Cluster Randomized Trial for Two Proportions Example.nqt 
  • Comparison of Balancing Properties Block Randomization Example.nqrl
  • Comparison of Balancing Properties Complete Randomization Example.nqrl
  • Comparison of Balancing Properties Wei's Urn Example.nqrl
  • Hierarchical Design with Level 2 Randomization Example.nqt
  • Parallel Design for Two Proportions Example.nqt
  • Parallel Design Z-test Two Means Example.nqt

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