Next course delivery: January to April 2025
Course description
This is a basic course in epidemiology which also covers a variety of analytic topics not commonly addressed in elementary statistics courses. This course will introduce students to the field of epidemiology. Students will critically evaluate articles in the epidemiologic literature and examine epidemiologic methods including:
- data collection
- study design and statistical analysis
- ratios
- relative risk
- contingency tables
- logistic and Poisson
- measurement error and exposure misclassification
- imputation of missing values
- multilevel regression models in epidemiology
Learning objectives
- Explain basic concepts in descriptive epidemiology such as incidence, prevalence, mortality, morbidity and effect.
- Distinguish among common epidemiological designs such as case-control, cohort, cross-sectional and randomized controlled studies.
- Identify major categories of bias that can affect the validity of epidemiological studies.
- Apply common measures of association such as relative risk, odds and odds ratios, attributable risk, attributable risk percentage and population attributable risk to epidemiological data.
- Employ common tools of epidemiological statistics such as logistic and Poisson regression and become oriented to multilevel regression models to analyze appropriate data.
Prerequisites
- Admission to the PSC in Population Health Data Analysis or permission of the Faculty Advisor.
- Working knowledge of basic statistical concepts (how to interpret P values, null hypothesis, and confidence intervals).
- Some experience with regression modelling and basic SAS programming (e.g., DATA step and procedures).
Instructor: Alvin Li
Alvin Li is currently a clinical epidemiologist for a real-world health data intelligence company. Prior to this role, he was a scientist at a provincial health organization focusing on applied research for cancer prevention. He has over 10 years of research experience and has conducted multiple projects using large health administrative datasets on various topics including kidney transplantation, immigrant health and the evaluation of health policies.
He completed his PhD in epidemiology and biostatistics at Western University and a postdoctoral fellowship at the Ottawa Health Research Institute. He has a strong interest in teaching and has also taught lessons on data analytics.
This program has been developed by Population Data BC in partnership with the Division of Continuing Studies, University of Victoria.
For further details, visit the Division of Continuing Studies webpage.
