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DEVELOPING INNOVATIVE STATISTICAL MODELS TO PREDICT CANCER INCIDENT CASES AND OUTCOMES AT THE SMALL-AREA LEVEL

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thesis
posted on 21.10.2021, 05:14 by Win Wah
Cancer incidence and outcomes vary across populations and geographies over time. Understanding the extent and causes of disparities is essential to cancer control. This thesis developed statistical models to predict cancer incident cases and outcomes at the small-area level. Studies described geographic and temporal patterns, examined factors explaining the variation, and performed projections in geographic areas. My thesis provides novel clinical contributions and methodological framework in terms of identifying factors that explain cancer disparities and quantify the existing and future burden of cancer at the small-area level, essential for cancer prevention and control. These models can be implemented in other cancers and diseases.

History

Principal supervisor

Arul Earnest

Year of Award

2021

Department, School or Centre

Epidemiology and Preventive Medicine

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Medicine, Nursing and Health Sciences

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