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GW4 BioMed MRC DTP PhD studentship: Causal inference methods for randomised trials

  • Full or part time
  • Application Deadline
    Monday, November 25, 2019
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

This project is one of a number that are in competition for funding from the ‘GW4 BioMed MRC Doctoral Training Partnership’ which is offering up to 18 studentships for entry in September 2020.

The DTP brings together the Universities of Bath, Bristol, Cardiff and Exeter to develop the next generation of biomedical researchers. Students will have access to the combined research strengths, training expertise and resources of the four research-intensive universities.


Lead supervisor: Dr Jonathan Bartlett, Department of Mathematical Sciences, University of Bath
Co-supervisors: Dr Rhian Daniel (Cardiff), Dr Daniel Farewell (Cardiff) and Dr Jack Bowden (Bristol)


The analysis and interpretation of randomised trials should in principle be straightforward: we compare the outcomes in those patients randomised to the novel treatment to the outcomes in those randomised to the control treatment. In practice things are more complicated. Patients may die before the outcome of interest can be measured. They may stop taking their randomised treatment or start taking other treatments.

What has traditionally been called the intention to treat effect estimates the effect of randomisation. Depending on the setting and stakeholder, this ‘estimand’ may not correspond to the scientific question of interest, particularly when for example treatment compliance in the trial is not reflective of what would be seen in routine clinical practice. Alternative estimands include those that estimate the effect if treatment compliance had been maintained somehow, or the effect in a sub-population who would have fully complied under randomisation to either treatment. Depending on the setting, there may be material differences in the magnitude, and potentially even direction, of different estimand effects, such that clear pre-specification of a trial’s estimand(s) is critical.

Within the pharmaceutical trials world, there has recently been vigorous debate and increased awareness of the importance of clear specification of estimands. This has led to the ICH E9 draft addendum on estimands. This addendum lays out a framework and terminology for qualitatively describing different estimands, but says little about the specifics of how each might be estimated statistically. It highlights in general terms the importance of clearly identifying what assumptions are needed to estimate a given estimand, but again says little about specific details. There is thus a pressing need to understand which existing statistical methods could be used to estimate different estimands and develop new ones where required.

This PhD project will involve exploration and development of statistical methods for estimating different types of estimand. This will likely involve a combination of exploiting existing methods developed in the causal inference and missing data literature together with development of new methods. It will likely involve a mixture of theoretical arguments based on statistical theory and simulation studies. In addition, real clinical trial datasets will be analysed to illustrate the methodological developments. Depending on the interests of the student, it may also involve development of accompanying statistical software to facilitate uptake of the methods by clinical trialists.

The papers and software generated during the proposed project would be expected to have immediate and tangible impacts on the design and analyses of both publicly funded and industry clinical trials.

After the PhD, the student will be extremely well placed to take their next career step in either academic research or industry.


Applicants for a studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an area appropriate to the skills requirements of the project.

IMPORTANT: In order to apply for this project, you should apply using the DTP’s online application form:

You do NOT need to apply to the University of Bath at this stage – only those applicants who are successful in obtaining an offer of funding form the DTP will be required to submit an application to study at Bath.

More information on the application process may be found here:


Funding Notes

A full studentship will cover UK/EU tuition fees, a Research and Training Support Grant of £2-5k per annum and a stipend (£15,009 per annum for 2019/20, updated each year) for 3.5 years.

UK and EU applicants who have been residing in the UK since September 2017 will be eligible for a full award; a limited number of studentships may be available to EU applicants not meeting the residency requirement. Applicants who are classed as Overseas for tuition fee purposes are not eligible for funding.

More information on eligibility may be found here: View Website

How good is research at University of Bath in Mathematical Sciences?

FTE Category A staff submitted: 44.40

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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