Next course delivery: January to April 2025
This course is now available to individuals residing outside of Canada. Please contact Program Coordinator, Ann Greenwood at firstname.lastname@example.org or 250-721-8627 for more information.
This fully online course will provide you with an introduction to—and hands-on experience including the use of a Secure Remote Training Lab — specifying multi-level modeling and longitudinal analysis. You will gain an understanding of different types of approaches including:
- time varying and invariant predictors
- multivariate and multi-population models with different outcomes
- missing data, errors in measurement and measurement misclassification
This course is designed to serve the needs of researchers who will analyze and model longitudinal data in population health research.
- Define the methodological features of longitudinal data analysis.
- Describe fundamental concepts and issues in multi-level modeling.
- Identify different analytical approaches to longitudinal data analysis and specify their strengths and limitations.
- Use Mplus statistical modeling program to perform longitudinal data analyses in population health research.
- Develop and practice longitudinal model specification, estimation, evaluation, and modification skills.
- Interpret and evaluate findings in longitudinal population health research.
- Admission to the PSC in Population Health Data Analysis or permission of the Faculty Advisor.
- Be comfortable with basic SAS programming (e.g., DATA step and procedures). Familiarity with Mplus will also be helpful.
- Be comfortable with linear regression models. Familiarity with generalized linear models such as logistic regression will also be helpful.
- If you would like to start pre-course SAS and or Mplus orientation before enrollment in this course, please contact Melissa Payne, PHDA Program Assistant, UVic Continuing Studies for further consultation at: email@example.com
Instructor: Monica Ye
Qian (Monica) Ye is a senior statistician working in the BC Centre for Excellence in HIV/AIDS (BC-CfE), Canada’s largest HIV/AIDS research, treatment and education facility. She completed her MSc, and is pursuing her PhD degree in statistics in the Department of Statistics at University of British Columbia, Vancouver. Her research interests lie in innovative statistical models analyzing longitudinal and survival data, and their applications in the field of epidemiology and public health.
In her current role at BC-CfE, Monica works with population-based administrative cohort data sets to support comprehensive research aiming to improve the health of British Columbians with HIV and related diseases. She has more than 10 years data analysis experience in both professional and academic fields, which involve a broad range of statistical methodologies and extensive programming using various statistical software including SAS, R, Python, etc.
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.