Cécile Proust-lima
  • E-mail :[email]
  • Phone : +33 5 57 57 45 79
  • Location : Bordeaux, France
Last update 2017-10-21 22:46:39.229

Cécile Proust-lima PhD, HDR Biostatistics

Course and current status

Current position
Researcher (CR1) since 2008 at Bordeaux Population Health Research Center, Inserm, Bordeaux, France.

Previous positions
2008 Research Assistant, Biostatistics and Nutrition departments, Inserm, Bordeaux, France.
2008 Assistant Professor, ISPED, Université Bordeaux Segalen, Bordeaux, France.
2007 Postdoctoral fellow, Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, USA.
2003-2006 PhD student and assistant professor, Inserm, ISPED, Université Bordeaux Segalen, Bordeaux, France.

2014 Qualification to direct Research (HDR), Université Bordeaux, France.
2006 PhD in Medical Sciences, Biostatistics specialty, Université Bordeaux Segalen, France.
supervised by Hélène Jacqmin-Gadda
2003 Master in Epidemiology and Public Health, biostatistics specialty, ISPED Université
Bordeaux Segalen, France.
1999-2002 National (Engineering) School for Statistics and Information Analysis, ENSAI, Rennes, France. specialty in Statistics for Life Sciences

Teaching activity (in Masters, summer schools, short courses)
Latent class mixed models, Longitudinal analysis of psychometric scales, (Generalized)
linear mixed models, Latent variable models, Joint models.

Involvement in the Scientific Society
Comittee of the French Biometrics Society since 2015
Comittee of the Health Research Department of the University of Bordeaux since 2014
Steering Group of the International Biometric Society Channel Network since 2014
Statistics and Mathematics applied to cancer research (SMAC) since 2013
International Methods in Longitudinal Research in Dementia (MELODEM) Initiative since 2012

Involvement in Scientific journals
Associate Editor for Biometrics since 2014, and Biostatistics since 2016

Scientific summary

My research focuses on the development of dynamic statistical models to describe, explain and predict chronic disease progressions.I specialized since my PhD in the joint analysis of correlated longitudinal markers and event time history using the so called joint models with applications in Alzheimer's disease, cerebral aging or some cancers.

In particular, I have developed approaches based on latent processes to translate psychometric concepts such as cognitive functioning or disability that may be measured by multiple repeated outcomes, and latent classes to translate the heterogeneity of disease progression. I have also contributed to the development of individual dynamic predictions that quantify the risk of experiencing a clinical event based on the dynamic history of an individual.

All my works are motivated by epidemiological and clinical questions thanks to strong collaborations with epidemiologists and clinicians in the research center and through international networks (e.g., MELODEM for Alzheimer's disease), and access to large cohort studies.

My statistical developments are made available in lcmm R package. It is maintained and new functionalities are gradually added.

Image d’exemple