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Modelling Growth Charts with Measurement Error: A Modern Perspective of Prediction of Abnormal Growth Responses in Young Children and Adults

Project Type: 
PDF-led

Using modern statistical measurement error methodologies and analysis, this project aims to efficiently and accurately discover and characterize predictive models of responses associated with abnormal growth development in young children and adults.

Project Leader(s): 

Postdoctoral fellow: Dr. Taraneh Abarin, Public Health Sciences, University of Toronto

Lead faculty member: Dr. Laurent Briollais, Public Health Sciences, University of Toronto

Using modern statistical measurement error methodologies and analysis, we aim to efficiently and accurately discover and characterize predictive models of responses associated with abnormal growth development in young children and adults. This proposal is unique in scope and vision by addressing health issues that threaten the sustainability of the health care system. It integrates the state-of-the-art statistical methodologies into novel analytic capability, incorporates the investigations of a world-leading team of reproductive scientists, provides Ontario researchers, through an international collaboration, access to a unique 21 year pregnancy cohort study (RAINE cohort), and focuses analysis of this Cohort on outcomes that can be directly applied to improve the health of young children and adults. It also offers through partnership with potential industry partners some opportunities to implement new screening and diagnostic capabilities into future pregnancy and child cohorts in Ontario, and thus positively impacts the health and well being of women and their children.