Please find below a great job opportunity in Tours (France) to work on time-to-event outcomes in cluster randomized trials.
Sent on behalf of Agnès Caille (This email address is being protected from spambots. You need JavaScript enabled to view it.)
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Post-doctoral researcher position in Tours, France
The INSERM SPHERE Unit U1246 is part of both the Universities of Tours and Nantes and aims to contribute to high-quality research in methods on patient-centered outcomes and health research. Equipe SPHERE
We are looking for a motivated scientific staff member to join our team and engage in our research project QUARTET.
The research project QUARTET deals with time-to-event outcomes in cluster randomized trials. Cluster randomised trials are trials in which intact social units, such as hospitals, medical practices or communities, are randomized to intervention or control conditions while outcomes are then assessed on individuals within such clusters. The use of cluster randomised trials to evaluate clinical and public health interventions has been rising in recent years.
In cluster randomised trials, outcomes assessed on individuals from a given cluster are correlated. This clustering has to be taken into account at the planning stage, leading to an increased sample size to reach the same power as a comparable individually randomized trial. Analysis methods of a cluster randomised trial must also account for the correlated nature of the outcomes within clusters. This can be done by using either mixed-effects models, in which clusters are treated as random effects, or marginal models estimated with generalized estimating equations (GEEs). When reporting the results of a cluster randomised trial, a measure of intracluster correlation should be reported, usually the intracluster correlation coefficient.
Most of the developments to quantify and account for clustering in the analysis of cluster randomised trials have considered continuous or binary outcomes. Conversely, limited methods and recommendations are available for time-to-event (TTE) outcomes. In practice, TTE outcomes in cluster randomised trials are often inappropriately analysed, by treating them either as clustered binary outcomes or as TTE outcomes but ignoring correlation. The performance of existing analysis methods for correlated TTE outcomes has not been compared in the context of cluster randomised trials and the intracluster correlation coefficient (or any other measure of intracluster correlation) for TTE outcomes has not been clearly defined.
The main objective of the QUARTET project is to identify optimal analysis methods for TTE outcomes in cluster randomised trials including appropriate methods of estimating the degree of clustering for TTE outcomes.
After searching the methodological and statistical literature to identify all available methods to analyse correlated TTE data, we will develop novel methods appropriate for cluster randomized trials where gaps are identified. Existing and novel methods will be compared by simulation. A similar approach will be used for measures of clustering. This later part of the project will consist of both theoretical work to develop new methods as well as computer simulation to evaluate methods. Finally, real data from three trials (for which we already have the agreement from the scientific coordinators) will be used to illustrate our findings.
Ease of use of the selected methods and ease of interpretation of the results produced by these methods will be evaluated by surveying a panel of clinicians and statisticians. We will use a Delphi method to reach consensus. The objective of this innovative step is to balance statistical properties with ease of use and ease of interpretation in the development of final guidelines for analysis and measures of clustering. Recommended methods will be implemented in user-friendly R packages to be available to the wider scientific community.
At the end, this project will provide practical guidelines for TTE outcomes in cluster randomised trials, with a special focus on balance between statistical aspects and interpretability for future users.
The post-doctoral researcher will work specifically on measures of clustering for time-to-event outcomes in cluster randomised trials. This will include analytical developments and simulations.
The position will include teaching activity and a master's thesis supervision.
The position will be based in the office space of the SPHERE unit in the teaching hospital of Tours, France. The applicant will have his/her own office with an adequately powered computer.
The candidate must have completed a PhD in a relevant discipline (e.g. biostatistics, medical statistics, bioinformatics). Knowledge in the methodology and the statistical analysis of randomised controlled trials and advanced programming skills in the statistical software program R/RStudio are a prerequisite. The candidate must be fluent in written and spoken English.
An experience in statistical methods for cluster randomised trials or any other situation with correlated data and/or an experience in survival analysis would be appreciated.
Further desirable elements are scientific writing skills as demonstrated by prior research publication and experience in simulation studies.
Please send all application documents (cover letter, curriculum vitae, etc.) to This email address is being protected from spambots. You need JavaScript enabled to view it.
The position will be open until filled. In order to receive full consideration, applications should be submitted by December 31st, 2020. The starting date is flexible, but no later than Spring 2021.
Do not hesitate to ask content related questions to Dr Agnès Caille This email address is being protected from spambots. You need JavaScript enabled to view it.
