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Elizabeth Turner

Assistant Professor, Biostatistics and Bioinformatics and Global Health
Trent 237
(919) 681-6226
Liz Turner


Liz joined the Duke Global Health Institute and the Department of Biostatistics and Bioinformatics in March 2012 to collaborate with, and provide biostatistical support to DGHI faculty and affiliates. With a PhD in statistics from McGill University, Canada, followed by four years working as a collaborative biostatistician in the Department of Medical Statistics, Faculty of Epidemiology and Population Health of the London School of Hygiene and Tropical Medicine (LSHTM), Liz has extensive experience working in both epidemiological studies and randomized trials across a range of substantive areas in developed world and resource poor settings.

Thanks to her participation in multi-disciplinary projects, she has a great appreciation for the importance of good study design and data collection and is well aware that no fancy statistical analyses can save researchers from the scourge of bad data. Through those experiences and her teaching in different settings, including the UK, Canada, France and Tanzania, she is aware that statisticians and their collaborators sometimes "speak a different language". As a result, her approach is very much one of translation, pragmatism and collaboration. Her current substantive interests include malaria, disability and disease burden with an emphasis on eye diseases, cardiovascular disease and mental health, together with child health and education.

Starting in fall 2013, Liz will teach the MSc-GH core course Introduction to Quantitative Research Methods for Global Health Science I.


Title Number Level
Biostatistics and Epidemiology for Global Health

Course introduces principles of epidemiology, including disease frequency measures; measures of association; observational, experimental, and quasi-experimental study designs; validity -- confounding, selection bias, measurement error; reliability. Course interweaves introductory biostatistics for continuous and categorical variables. Course has a data analysis lab section in which students walk through a guided data analysis on a provided data set, such as Demographic and Health Surveys.

Course Notes:
Was: GLHLTH 320


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