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ALLSTAT  February 2010

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Subject:

JOB: PhD studentship

From:

Deborah Ford <[log in to unmask]>

Reply-To:

Deborah Ford <[log in to unmask]>

Date:

Wed, 17 Feb 2010 15:54:13 +0000

Content-Type:

text/plain

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MRC Clinical Trials Unit, London
PhD Studentship in Medical Statistics 

Efficacy Analysis for Trials with differential use of alternative "second-line" 
treatments
Stipend £15,930 per annum 
Supervisors: Dr Deborah Ford & Dr Sarah Walker 

The award covers fees and a tax-free maintenance stipend over three years. 
In the first year the stipend is £15,930. 

An MRC-funded PhD studentship is available at the MRC Clinical Trials Unit 
commencing October 2010 for study on the Efficacy Analysis for Trials with 
differential use of alternative "second-line" treatments.  

Intention to treat analysis (ITT) is recognised as the standard approach for 
comparing treatments in a randomised controlled trial (RCT). Post-
randomisation variables such as prescription of alternative treatments are 
usually ignored. An ITT effect therefore estimates the policy effect of starting 
treatment with treatment A versus treatment B and includes subsequent 
indirect effects which may differ between randomised arms; for example use of 
second-line treatment, on the assumption that these alternate treatments 
would be used similarly outside of a trial. 

The question remains as to how much any difference (or lack of difference) 
between two randomised first-line treatments might be due to differential use 
of second-line. Differential use of second-line treatment may not be adjusted 
appropriately for by censoring at initiation of second-line or by adding use of 
second-line as a time-dependent covariate in a standard Cox model because 
these simple adjustments fail to allow correctly for time-dependent 
confounding. Causal models are necessary to estimate the difference between 
randomised groups that would have been observed if use of second-line had 
been the same in randomised groups, i.e. to estimate the direct treatment arm 
effect. Additionally the benefit of (non-randomised) second-line therapy may 
be jointly estimated.

This is an applied statistics project which would allow you to become familiar 
with causal modelling methodology and to apply different methods to address 
clinically relevant questions in HIV and cancer data sets.       

You will join the group of PhD students within the MRC London Hub for Trials 
Methodology research.  You will register for full-time MPhil/PhD study at the 
Research Department of Infection and Population Health, University College 
London.

You will have a minimum of a 2.1 BSc degree in statistics or mathematics. An 
MSc in statistics or medical statistics is desirable. Following MRC restrictions, 
full studentships are available only to UK applicants. Other EU applicants may 
be eligible for a "fees-only" award. 

For an informal discussion about this post please contact Dr Deborah Ford – e-
mail [log in to unmask]


Applications for this role should be made online at http://jobs.mrc.ac.uk.  If 
you do not have internet access or experience technical difficulties, please 
call 01793 301154 quoting the reference number CTU10/072.   When applying 
online please complete the cover letter section clearly stating, with examples, 
why you would like to be considered for this studentship and how you meet 
each of the criteria listed in the Person Specification. Please also supply a CV 
and the details of two academic referees.

If you would like to receive this advert in large print, Braille, audio or 
electronic format/hard copy, please contact the Recruitment team at the MRC 
Shared Service Centre on the telephone number above or email 
[log in to unmask]

Closing Date: 5th March 2010  

The Medical Research Council is an Equal Opportunities Employer and operates 
a strict no smoking policy.

You may leave the list at any time by sending the command

SIGNOFF allstat

to [log in to unmask], leaving the subject line blank.

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