An unprecedented model in France combining a university, a university hospital (CHU de Nantes), a technological research institute (IRT Jules Verne), a national research organization (Inserm) and the Grandes Écoles (Centrale Nantes, École des Beaux-arts Nantes Saint-Nazaire, Ecole Nationale Supérieure d'Architecture de Nantes)
Commitment to professional equality, diversity and inclusion and addressing gender-based and sexual violence
Membership in the EUniWell European Alliance committed to wellness
Certified HR Excellence in Research since 2022 as part of the HRS4R strategy
Faced with a major life event, people may change how they interpret and evaluate their anxiety or quality of life when responding to self-reported outcomes, a phenomenon called response shift. Most of response shift analyses based on statistical methods consider two
measurement occasions. Yet, changes of self-reported outcomes over time are often assessed over multiple time points. In this context, the trajectory of the construct is continuons by essence and response shift could be envisioned as a continuons process.
Furthermore, the study timescale has often to be treated as continuons rather than as discrete with equally spaced time points. Methods capable of detecting and adjusting for response shift over multiple time points in studies with continuons timescales are lacking.
The U1246 SPHERE research unit of Nantes Université is seeking a talented post-doctoral researcher to join us to develop a method for response-shift analysis at the item level in longitudinal self-reported outcomes studies across multiple time points. The post-doctoral grant (full-time, 22 months) is sponsored by the French National Research Agency (ANR). Objectives and missions :
- Propose an item-level response shift détection method based on continuous-time Raschmodels
- Perform simulation studies to assess the performance of the method
- Develop open-source solutions to disseminate the method to the widest possible audience
- Work data visualization preferences and understanding of the results to promote knowledge translation
Work environment
The methodS in Patient-centered outcomes & HEalth ResEarch (SPHERE - UMR 1246) research unit aims to strengthen the development of methods for patient-centered health research in a multidisciplinary perspective. The unit is structured into four thematic axes. The project will be embedded within Axis 3, dedicated to methods for the measurement and interprétation of Self-Reported Outcomes.
We offer :
A stimulating multidisciplinary environment
Access to a high-performance scientific computing environment
Travel opportunities for attending scientific conférences
Opportunities to gain experience in statistics teaching (if desired)
Education and research background:
PhD in biostatistics or psychometrics
Previous experience in health research and psychometrics is mandatory
Technical skills :
Strong knowledge of latent variable models
Good skills in simulation studies
Proficiency in Statistical programming in R or Stata
Excellent written and verbal communication skills in English
Professional qualities :
Strong ability to propose original research directions and methodological approaches
Open science practices will be appreciated
The candidate must send the following material in English :
A curriculum vitae including educational background, professional experience, and contact information for two references
A list of publications
A cover letter