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Apologies for cross-posting See below for details of two statistics PhD studentships in the Centre for Health Sciences, Barts & The London School of Medicine & Dentistry, Queen Mary University of London, based in Whitechapel. Please forward to anyone who you think might be interested. Applicants should have at least an upper second class bachelor’s degree with a high level of statistical content, or a master’s degree in statistics, and should have a strong interest in medical statistics. These studentships offer an exciting opportunity to be part of a growing team of highly motivated statisticians within a UK National Institute of Health (NIHR) registered and funded Clinical Trials Unit, the Pragmatic Clinical Trials Unit (PCTU) (www.ihse.qmul.ac.uk/chs/pctu/index.html). The PCTU carries out a wide range of clinical trials but also conducts methodological work mostly in practical applications to support the design, conduct and analysis of pragmatic clinical trials. The Centre in which the PCTU is situated has over 15 years’ experience in conducting trials and was rated fourth in the UK in health services research in the 2008 Research Assessment Exercise. The successful applicants will join a group of eight statisticians, and will have extensive training opportunities both in research and statistical methods as appropriate. The Centre currently hosts 14 PhD students across of range of disciplines within community health sciences. Both studentships are funded full-time for three years by the Medical Research Council, and come with a tax-free stipend of £15,590 per annum. They are open to UK Nationals, EEA/Swiss migrant workers and non UK nationals with indefinite leave to remain in the UK who all have three years’ ordinary residence in the UK prior to the start of the studentship. Projects are due to commence on 1 October 2011. Note the two projects have different arrangements for applying - please read the information given below for the project you are interested in. PROJECT 1 Title: Choosing covariates in the analysis of cluster randomised trials Co-supervisors: Dr S Bremner & Professor S Eldridge This studentship focuses on cluster randomised trials, which are increasingly popular in health services research. A gap in knowledge in relation to such trials is determining which covariates to include in the trial analysis. Appropriate procedures are better understood in individually randomised trials, but in cluster randomised trials covariates can occur at two levels, the cluster and the individual level, and there may be complicated relationships between covariates at different levels. There has been a small amount of work in this area but a comprehensive review is needed particularly for non-continuous and non-normally distributed outcomes. This studentship offers the chance to explore existing literature in this area both for individually and cluster randomised trials, to use data from some of the many cluster randomised trials within the PCTU to understand empirically the relationships between different covariates and outcomes, and use simulation to explore these relationships further. The student will gain knowledge and experience in these three areas, and develop highly relevant guidelines for clinical trial investigators, a priority area for NIHR research. For an informal discussion about this project, please contact Dr Stephen Bremner Tel: 020 7882 2547 Email: [log in to unmask] The closing date for applications is 14 February 2011. To apply, please download the School of Medicine & Dentistry application form from our website: http://www.qmul.ac.uk/postgraduate/apply/index.html and return to the Graduate School Office - email: [log in to unmask] Please note that we accept postal and electronic applications. Referees may email references directly to [log in to unmask] PROJECT 2 Title: Statistical methods for analysing discordance trials of biomarkers or other diagnostic tests Co-supervisors: Professor Sandra Eldridge & Dr Richard Hooper Diagnostic tests are usually studied in terms of their accuracy – how often they correctly diagnose disease – but in practice the test result will be used to make decisions about the management of patients, and a clinical trial may therefore be the most appropriate way to compare two diagnostic tests. There is a rapidly growing interest in the use of tests to guide treatment choices rather than specifically to diagnose: biological tests of this kind are called biomarkers, and are seen as a key element of an approach to healthcare known as stratified medicine, in which a treatment is matched to a patient in order to optimise its effect. It has been suggested that an efficient approach to trialling is to give both tests to all participants, and to randomise and follow up those with discordant results. We are interested in putting these ideas into a more formal framework. The regulatory authorities who oversee new treatments require that any new treatment tool – including a biomarker – must be validated using a large Phase III clinical trial before it can be accepted as the standard of care. Although there have so far been relatively few such trials comparing the use of a biomarker with a non-stratified control, and almost none comparing two biomarkers, this sort of application is likely to blossom as stratified medicine takes off, and more and more biomarkers begin to be investigated for their use in treatment decision-making. Our theoretical work has already allowed us to put a figure on the huge efficiency saving of a discordance trial design over a conventional trial for comparing two biomarkers or other diagnostic tests. We found a four-fold reduction in the number of trial participants required using figures from one published protocol as an example (with a further reduction in the number whom it was necessary to follow up). There are clear ethical and financial imperatives to adopting such an efficient design in trials, but the details of the statistical methods that should be used are still unclear, creating an obstacle to the development of trials of this kind. Much more work is needed to show how to extend the standard generalised linear modelling approach used for binary, continuous and survival outcomes in conventional trials to the context of a discordance trial. This would provide the focus of the PhD project. For an informal discussion about this project, please contact Dr Richard Hooper Tel: 020 7882 7324 Email: [log in to unmask] This is one of a number of studentships being advertised together by Barts & The London School of Medicine & Dentistry, for which students will be selected by competition. The closing date for applications is 20 February, and interviews will be held on 14 March. To apply, go to http://www.smd.qmul.ac.uk/graduatestudies/index.html, click on the button marked "PhD studentships currently available", and follow the instructions. You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.