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Last Updated: Oct 12, 2017 URL: http://theta.utoronto.ca/HomePage Print Guide

Kuan Liu Profile Print Page
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Kuan Liu Profile

 

Kuan Liu, MMath, PhD (candidate)

Biostatistician

 

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Program of study
Kuan is currently a PhD student majoring in Biostatistics at Dalla Lana School of Public Health, University of Toronto and a graduate practicum student at THETA supervised by Dr. George Tomlinson.
 
Education and Training
Kuan completed her Bachelor Honor degree in Statistics at University of Alberta and her Master of Mathematics degree in Biostatistics at University of Waterloo. Before starting her PhD study at University of Toronto, Kuan worked full time as a research Analyst at the Institute for Clinical Evaluative Sciences, Western Satellite site for almost 3 years. At ICES western, Kuan participated over 20 ICES projects where she was intensively involved in the study design, statistical analyses and manuscript preparation processes. Kuan currently holds the SickKids Research Training Competition Scholarship and is the appointed Student co-chair of the student and recent graduate committee of the Statistical Society of Canada.
 
Research Interests and Expertise
His research interests focus on statistical methods for economic evaluation and health economics. He is currently working on developing statistical methods for mapping the descriptive quality of life instrument for myelofibrosis patients using MFSAF and MPN-SAF to EQ-5D which is a utility instrument. He is also interested in economic evaluations in HTA such as cost-effectiveness analysis, net-benefit analysis, etc.

Projects
As a practicum student at THETA, Kuan will be working closely with Dr. George Tomlinson to complete pilot studies on the safety and efficacy assessment of the current consensus treatments on pediatric arthritis, a project funded by the Childhood Arthritis and Rheumatology Research Alliance.

Research Interest
Developing new biostatistics methods that permit causal inference from complex longitudinal studies. For her PhD thesis, Kuan plans to explore Bayesian causal inference methods that could handle irregular longitudinal data with time-dependent treatment allocations and covariates.

Publications
Kuan's Research Gate Profile 

Supervisors 
Dr. George Tomlinson

 
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