Dear all,
The Biostatistics Unit, Centre for Epidemiology and Biostatistics, has the following prestigious
(3+1 years) full-time studentship available from 1st September 2008, funded by the Medical Research
Council. This capacity-building studentship will support a 1-year MSc in Health Research, followed
by a 3-year PhD in Statistical Epidemiology.
Please see below for further details of the application procedure.
Best regards,
Paul
*********************************************************************************************
MRC Capacity Building Research Studentship
Biostatistics Unit, Centre for Epidemiology and Biostatistics, Faculty of Medicine and Health,
University of Leeds
Improved statistical modelling for observational research: understanding and addressing the problems
associated with collinearity
Supervisors: Professor Mark S Gilthorpe, Dr Paul D Baxter, Dr Yu-Kang Tu
Sponsor: MRC / University of Leeds
Email: [log in to unmask]
Tel: 0113 343 7497
Collinearity amongst covariates in linear regression models has long been recognised as a potential
source of bias. Various ‘solutions’ have been proposed, though one important issue almost entirely
omitted in the current literature is the importance of the relationship between the outcome and
correlated covariates. Using vector geometry, it can be shown that the impact of collinearity on
the model, such as changes in regression coefficients, cannot be judged by the correlation structure
of the covariates alone – their relationship with the outcome is crucial. Traditional diagnostics
of collinearity are thus insufficient in evaluating adverse effects or model instability.
The challenges for the student are to develop new diagnostic tools to evaluate the extent of
collinearity in statistical models, both beneficial (appropriate adjustment for confounding) and
adverse (bias). For generalized linear models, further theoretical work is needed to develop a
statistical index to characterize associations between the outcome and all collinear covariates.
Theoretical derivations and computer simulations are needed to evaluate the extent of collinearity.
The student is then required to implement these new methods in statistical packages, such as R or
Stata, to provide a clear illustration to general users of statistics how to quantify beneficial and
adverse collinearity in their statistical model. Simulations and genuine data will be used to test
the validity of these new methods. Most covariates in epidemiology and public health are collinear,
and the implementation of these methods will enable biomedical researchers to develop more
appropriate models to provide robust research findings. This studentship is therefore anticipated
to have a huge impact on the statistical modelling undertaken in these fields.
Students are required to have at least an upper second class degree in mathematics, statistics or
related subject, and an interest in applied methodology in biomedical research. The candidate will
receive basic training towards an MSc in Health Research, involving basic epidemiology and
statistical epidemiology. Informal inquires regarding this studentship can be directed to either
Professor Gilthorpe ([log in to unmask]; Tel 0113 343 1913) or Dr Baxter
([log in to unmask]; Tel 0113 343 5162). Further details about the research interests of the
group can be found at http://www.leeds.ac.uk/medhealth/light/research/deb/biostatistics/index.html.
Candidates must be eligible for UK/EU fee status (EU students MUST have been in the UK for at least
three years prior to commencement of studentship, or being ‘migrant workers’ at the time of
application). More details about eligibility criteria are available from
http://www.mrc.ac.uk/Careers/Studentships/ForStudents/FinancialSupport/index.htm). The studentship
will cover full fees for UK/EU students, a research training support grant, conference allowance,
and a maintenance stipend (approximately £14,600 per year). Applicants should send a statement of
interest (no more than 1 page) and a CV with the names and contact details of two academic referees
to Miss Claire Walton (Postgraduate Research Student Co-ordinator, Faculty Graduate School, Room
10.110, Level 10, Worsley Building, Leeds LS2 9NL) by Wednesday 30th April 2008.
--
Dr. Paul D. Baxter University of Leeds,
Lecturer in Statistics Department of Statistics,
web: http://www.maths.leeds.ac.uk/~pdbaxt Leeds, LS2 9JT, UK
phone: (+44) (113) 343 5162 fax: (+44) (113) 343 5090
|
