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3-year PhD position in Biostatistics, Tours, France

  • 13 Jul 2021 11:56 AM
    Message # 10747409
    Jessica Kasza (Administrator)

    Please find below the details of a fully-funded PhD position in Tours (France): "Estimating complex intervention effects as risk differences in cluster randomised trials". 

    If you wish to apply or if you would like more information, please contact Prof. Bruno Giraudeau bruno.giraudeau `at'


    3-year PhD position in biostatistics
    Tours, France
    Estimating complex intervention effects as risk differences in cluster randomized trials

    Cluster randomized trials (cRTs) are defined as randomized trials in which clusters of
    individuals are randomized rather than individuals themselves. Such trials may be conducted
    in clinical settings and thus randomize practices, health professionals, wards, hospitals, etc. or
    non-clinical settings and randomize schools, families, residential areas, worksites, etc. The
    most compelling reason for cluster randomization is that the intervention cannot be delivered
    individually, for instance, for education interventions of healthcare practitioners, for most
    health service interventions or for health promotion interventions such as education programs
    using general media (i.e., TV, radio, etc.). As an example, the Printemps study assesses a
    tailored promotion intervention of a mobile application and website that offer evidence-based
    content for suicide prevention. Most of the interventions assessed in cRTs are said to be
    complex interventions, which means that they have several components. As an example, an
    intervention aimed at reducing the use of antipsychotic drugs in nursing homes could involve
    a health professional education program, the implementation of a new prescription tool, and
    the distribution of leaflets to staff.
    Randomizing clusters leads to hierarchical data: participants are embedded in clusters,
    which are randomly allocated to groups. As a consequence, there exists a correlation in data,
    which are then classically analyzed using a modelling approach such as a mixed model or
    generalized estimating equation. When the outcome is binary, a logit link function is
    classically used, which leads to expressing the intervention effect as an odds ratio. However,
    because expressing an intervention effect on a relative scale is associated with an overoptimistic
    appraisal of the result, results should be reported both as absolute and relative
    effect sizes. For binary data, this involves assessing a risk difference.
    The objective of this PhD position is to identify the statistical approach with the best
    statistical properties (Type I error rate, bias, coverage rate, power) to estimate an adjusted risk
    difference from correlated clustered data, considering a two-parallel group cRT.
    Assessing the statistical properties of the different identified methods will involve
    simulation studies. Results will be illustrated by using real data from cluster trials. As
    examples, the Ambroisie study assessed a strategy of gastric emptiness peri-extubation in
    intensive care unit patients, the Pralimap study assessed interventions aimed at preventing
    obesity in adolescents in grade 9 and 10, and the Apache 3 study compared two strategies to
    motivate unscreened women to participate in a whole cervical-cancer screening program.

    ESCIENT project
    This PhD position corresponds to one of the work-packages of the ESCIENT project, funded
    by the French National Agency of Research (ANR – AAPG 2021). The ESCIENT project
    focuses on estimating a complex intervention effect when the outcome is binary:
    Complex interventions include several components that may interact with one another.
    In health service and public health research, they are often assessed with cRTs, which
    randomize intact social units. In these trials, which population to be analyzed is a
    challenging issue. The boundary between lack of compliance and adaptation of the
    intervention to the context is tenuous; participants may lack compliance because of
    their own will or because of external events; because the intervention may be adapted
    to the context, an “as-treated” population is also of interest. We definitely need
    guidelines on this issue. From a statistical viewpoint, such trials are also challenging.
    An adjusted risk difference is the preferred way of expressing results, whereas
    classical statistical analyses usually return odds ratios. We presently lack clear
    recommendations on the optimal statistical method to be used. The ESCIENT project
    aims to close these two gaps.

    Two research units are involved in this project: the unit methodS in Patient-centered outcomes
    and HEalth ResEarch (SPHERE, involves experts of cRTs and
    APEMAC ( involves experts of complex interventions.

    The PhD student will join the INSERM U1246 research unit. This unit, entitled SPHERE
    ( is jointly accredited by the universities of Tours and Nantes as well
    as INSERM. It is a multidisciplinary unit that aims to develop and validate methods that can
    be used in clinical or epidemiological studies. Researchers work considering a
    pluridisciplinary perspective involving biostatistics, public health, clinical disciplines
    (addictology, dermatology, general practice, nephrology), pharmacology, health psychology,
    and health economics. The director is Véronique Sébille (University of Nantes), and Bruno
    Giraudeau (University of Tours) is the deputy director.

    Bruno Giraudeau will supervise the PhD candidate. He is a professor of biostatistics
    ( and works both at the University and Hospital of
    Tours. The PhD student will be located in Tours, and the doctoral school will be the Health,
    Biological Sciences and Life Chemistry doctoral school.

    Because this PhD position is part of a larger project, there will be interactions with other
    - researchers from the APEMAC research unit involved in the ESCIENT project: Nelly
    Agrinier, Laëtitia Minary and Joëlle Kivits (Nancy, France)
    - members of the scientific committee who are experts in cRTs: Monica Taljaard
    (Ottawa, Canada), Sandra Eldridge (London, UK), Elisabeth Turner (Duke, USA) and
    Agnès Caille (Tours, France).

    The net salary will be about 1700€/month. Of note, in Tours, a flat can be rented for 400€ to 500€/month.

    Annual tuition fee

    Starting date
    Fall 2021

    Completion of a MSc in biostatistics, medical statistics.
    Advanced programming skills in the statistical software program R.

    Living in Tours
    With about 136 000 inhabitants (360 000 in the
    conurbation), Tours is a human-scale city pleasant to live in.
    It is a charming student town (30 000 students at the
    university), benefiting from mild weather along the Loire
    river. Near famous castles such as Chenonceau, Chambord,
    Villandry or the Clos Luce where Da Vinci rests, Tours is
    just a one-hour train ride from Paris.

    Bruno Giraudeau
    •: INSERM U1246 - SPHERE
    2ième étage du bâtiment tertiaire
    CHRU de Tours
    2 Bd Tonnellé
    37044 Tours cedex 9
    @: bruno.giraudeau `at'

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