Evaluating and applying advanced statistical methods for hierarchical composite outcomes (Win Ratio) in complex intervention trials in low-and middle-income countries

About the project

About the Project Applications are now open for a unique studentship opportunity based in Pakistan. The NIHR-funded ACROSS (Affordable Cardiac Rehabilitation: An Outreach Inter-Disciplinary Strategic Study) aims to develop a culturally adapted and affordable home-based rehabilitation programme for people with multiple long-term health conditions including heart disease and anxiety/depression. We aim to evaluate the acceptability, clinical effectiveness, and cost-effectiveness of the programme's implementation in Pakistan and Bangladesh to determine its scalability and sustainability. We are looking to recruit an outstanding student to undertake a fully funded, full-time 3-year biostatistics PhD project to develop and apply innovative statistical methods to evaluate complex, patient-centred outcomes within a large multi-country randomised controlled trial. Applicants should be fluent English speakers (Masters Degree desirable) and must either already be resident in Pakistan or prepared to live there for the duration of the project. The successful candidate will focus on the use and optimisation of the Win Ratio approach to analyse hierarchical composite endpoints, using data from the ACROSS external pilot to inform the design and analysis of the definitive trial. The project is organised around three linked strands. The first is a structured scoping review of how hierarchical composites, and the Win Ratio in particular, have been specified, analysed, and reported in randomised trials, identifying methodological gaps and design choices relevant to ACROSS. The second develops optimal modelling, estimation, and power calculation, including handling of ties and censoring, covariate adjustment, stratified analyses to accommodate heterogeneity between Pakistan and Bangladesh, sample size methods evaluated through simulation using pilot data, and comparison with related approaches such as win odds and generalised pairwise comparisons. The third addresses missing data for hierarchical composites, an area that remains underdeveloped, through imputation strategies that respect the Win Ratio comparison structure and sensitivity analyses under departures from missing-at-random. Working within an international multidisciplinary team spanning biostatistics, cardiology, and global health, the student will gain training in advanced trial methodology, simulation study design, estimand-based inference under ICH E9(R1), and statistical computing in R and Stata. The studentship offers direct impact on the design and delivery of large-scale trials in low- and middle-income countries. Matriculation will be with the University of Manchester; the successful applicant will be based at our host institution, Pakistan Institute of Living and Learning, and will also benefit from a local academic supervisor under a split-site study arrangement. The studentship is fully funded, University registration fees are covered, and stipend payments will be provided at the applicable local rate. For informal enquiries please contact Dr Amy Blakemore at amy.blakemore@manchester.ac.uk or the ACROSS research programme at global-across@glasgow.ac.uk . Entry Requirements Applicants are expected to hold a minimum upper second class undergraduate honours degree (or equivalent). A Masters degree, in a relevant subject (e.g., statistics, biostatistics, medical statistics, epidemiology, mathematics, or data science) is desirable. Applicants from quantitatively oriented public health, health economics, or clinical research programmes will also be considered where the degree included substantive statistical training. Demonstrable experience of statistical programming in R and/or Stata. ILETS 6.5 (6.0 all components). How to Apply For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website ( https://www.bmh.manchester.ac.uk/study/research/apply/ ). Interested candidates must first make contact with the Primary Supervisor prior to submitting a formal application, to discuss their interest and suitability for the project. On the online application form select PhD Biostatistics . Equality, Diversity & Inclusion Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/

Research areas