[FG] Chammartin FrédériqueHead of Research Unit Dr. Frédérique Chammartin, Dr.OverviewMembersPublicationsProjects & CollaborationsProjects & Collaborations OverviewMembersPublicationsProjects & Collaborations Projects & Collaborations 3 foundShow per page10 10 20 50 ESTIMATE Research Project | 3 Project MembersThe goal of the ESTIMATE project is to improve the quality of work disability evaluations used in disability benefit decisions. This will be achieved by building a large, representative database of residual work capacity ratings and developing a Bayesian hierarchical model to produce more accurate and reliable estimates. A dataset published in 2021 is currently being re-analyzed using Bayesian methods to demonstrate the advantages of Bayesian hierarchical modeling. This approach allows for quantification of uncertainty in residual work capacity estimates and applies shrinkage toward a common mean by enabling groups to share information through hyperpriors. Towards an efficient use of available data in clinical research: Development, validation, and implementation of innovative statistical approaches in causal inference Research Project | 4 Project MembersThis project develops and enhances G-methods to improve causal inference in clinical research by combining longitudinal data with advanced statistical techniques, addressing time-varying treatments, confounders, and spatial correlations. ComBaCaL: Community-based Chronic Care Lesotho Research Project | 13 Project MembersCommunity-based Chronic Care Lesotho is a five-year implementation research project addressing chronic disease care in remote villages in rural Lesotho. In a cohort of over 100 villages we assess through cluster-randomized trials within cohorts (TwiCs) different innovative models where ehealth assisted lay community health workers provide care for hypertension, diabetes and HIV. 1 1 OverviewMembersPublicationsProjects & Collaborations
Projects & Collaborations 3 foundShow per page10 10 20 50 ESTIMATE Research Project | 3 Project MembersThe goal of the ESTIMATE project is to improve the quality of work disability evaluations used in disability benefit decisions. This will be achieved by building a large, representative database of residual work capacity ratings and developing a Bayesian hierarchical model to produce more accurate and reliable estimates. A dataset published in 2021 is currently being re-analyzed using Bayesian methods to demonstrate the advantages of Bayesian hierarchical modeling. This approach allows for quantification of uncertainty in residual work capacity estimates and applies shrinkage toward a common mean by enabling groups to share information through hyperpriors. Towards an efficient use of available data in clinical research: Development, validation, and implementation of innovative statistical approaches in causal inference Research Project | 4 Project MembersThis project develops and enhances G-methods to improve causal inference in clinical research by combining longitudinal data with advanced statistical techniques, addressing time-varying treatments, confounders, and spatial correlations. ComBaCaL: Community-based Chronic Care Lesotho Research Project | 13 Project MembersCommunity-based Chronic Care Lesotho is a five-year implementation research project addressing chronic disease care in remote villages in rural Lesotho. In a cohort of over 100 villages we assess through cluster-randomized trials within cohorts (TwiCs) different innovative models where ehealth assisted lay community health workers provide care for hypertension, diabetes and HIV. 1 1
ESTIMATE Research Project | 3 Project MembersThe goal of the ESTIMATE project is to improve the quality of work disability evaluations used in disability benefit decisions. This will be achieved by building a large, representative database of residual work capacity ratings and developing a Bayesian hierarchical model to produce more accurate and reliable estimates. A dataset published in 2021 is currently being re-analyzed using Bayesian methods to demonstrate the advantages of Bayesian hierarchical modeling. This approach allows for quantification of uncertainty in residual work capacity estimates and applies shrinkage toward a common mean by enabling groups to share information through hyperpriors.
Towards an efficient use of available data in clinical research: Development, validation, and implementation of innovative statistical approaches in causal inference Research Project | 4 Project MembersThis project develops and enhances G-methods to improve causal inference in clinical research by combining longitudinal data with advanced statistical techniques, addressing time-varying treatments, confounders, and spatial correlations.
ComBaCaL: Community-based Chronic Care Lesotho Research Project | 13 Project MembersCommunity-based Chronic Care Lesotho is a five-year implementation research project addressing chronic disease care in remote villages in rural Lesotho. In a cohort of over 100 villages we assess through cluster-randomized trials within cohorts (TwiCs) different innovative models where ehealth assisted lay community health workers provide care for hypertension, diabetes and HIV.
