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Random allocation methods and implications for statistical analysis

   Population Health Sciences Institute

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  Dr Tom Chadwick, Dr Mike Cole, Dr Matthew Breckons  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Background: The utilisation of random allocation procedures is essential in clinical trials. Efficiency in the estimation of the treatment effect can be achieved by stratified permuted block randomisation, where stratification factors are likely to identify homogeneous subgroups of participants. Such blocking has the additional benefit that the number of participants with the specific stratification factor characteristics are relatively balanced between the trial arms. However, there are limits to the number of factors that can be practically accommodated. Minimisation is an alternative, somewhat controversial method that has become increasingly popular as it offers a means to directly control the imbalance of several prognostic factors between arms. In some clinical applications minimisation has become an accepted method of treatment allocation however it remains unclear whether it achieves its stated aims.

Statistical analysis needs to reflect the treatment allocation method used. It is well accepted that when stratified block randomisation is used, the stratification factors should be adjusted for in the statistical analysis. Some have argued that the same is true when minimisation is used. In some circumstances however, this would not be feasible; a small sample size and a large number of minimisation factors, for example.

What the studentship will encompass: This studentship will aim to explore the design and analysis of trials using minimisation or stratified block randomisation with a view to producing evidence-based recommendations for practice.

The first stage will be to systematically review the published literature on the two approaches and identify gaps in the evidence on why specific allocation methods are preferable. Stage two will engage with stakeholders (e.g. research groups and trial design teams) to understand why some research groups favour one system over another; understanding these different perspectives is of importance and, in particular, how these views may inform methodological practices. This stage will identify barriers or evidence gaps that may be required to inform and change practice. Stage three will be guided by the gaps and challenges identified in the earlier stages. This will involve using real world existing trial protocols, theoretical scenarios and simulation methods to assess the impact of the randomisation strategies on the efficiency of the design and the statistical analysis and to be able to recommend best practice.

 The supervisory team together span a broad range of trial designs and methodological expertise including experience of randomised clinical trials using both allocation methods we propose to consider. DT is Professor of Biostatistics and Deputy Director of the Newcastle Clinical Trials Unit. TC is a Clinical Trials Statistician and a specialist RDS adviser. MC is a statistician with over 30 years’ experience of applied clinical research. MB is a Research Associate at Newcastle University with extensive experience of conducting PPI work to inform research methods (including randomisation procedures) and stand-alone and nested qualitative studies.

We propose to include input from patients/public to explore how to explain the various allocation methods and additionally to address any possible concerns over imbalance or other concerns raised.

In addition to PPI, fieldwork will include qualitative data collection from researchers regarding views on statistical practices and emerging evidence. This is likely to take the form of a mixture of focus groups and one to one interviews, either face to face or remotely dependent on participant preferences and current Covid-19 guidelines.

Candidates will need to have a training background in statistics, demonstrated by a numerate first degree with a substantial statistics component.


You are applying for a PhD studentship from the MRC TMRP DTP. A list of potential projects and the application form is available online at:

Please complete the form fully. Incomplete forms will not be considered. CVs will not be accepted for this scheme.

Please apply giving details for your first choice project. You can provide details of up to two other TMRP DTP projects you may be interested in at section B of the application form.

Before making an application, applicants should contact the project primary supervisor to find out more about the project and to discuss their interests in the research.

The deadline for applications is 4pm (GMT) 18 February 2022. Late applications will not be considered.

Completed application forms must be returned to: [Email Address Removed]

Informal enquiries may be made to [Email Address Removed]

Funding Notes

Studentships are funded by the Medical Research Council (MRC) for 3 years. Funding will cover tuition fees at the UK rate only, a Research Training and Support Grant (RTSG) and stipend (stipend to include London Weighting where appropriate). We aim to support the most outstanding applicants from outside the UK and are able to offer a limited number of bursaries that will enable full studentships to be awarded to international applicants. These full studentships will only be awarded to exceptional quality candidates, due to the competitive nature of this scheme.
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