Next course delivery: May to July 2021
This course is now available to individuals residing outside of Canada. Please contact Program Coordinator, Ash Moosavi at firstname.lastname@example.org or 250-721-8779 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.
- Knowledge of regression analysis is a requirement for this course.
- Although not required, some familiarity with SAS and Mplus software would be helpful.
Instructor: Laura Holder
Laura Holder is a Senior Analyst with the Analytics and Special Projects team at the Western Office of the Canadian Institute for Health Information (CIHI). She completed her M.Sc. in Epidemiology and Biostatistics in the Public Health Sciences Department at Queen’s University, Ontario. Her graduate research focused on how best to employ statistical methodologies to handle missing data in complex survey settings and the impact these methodological choices have on the conclusions drawn in studies. Prior to her role at CIHI, Laura worked as an analyst with the Institute for Clinical and Evaluative Sciences (ICES), where she used administrative health data to conduct the analyses for a broad range of studies. These included international comparisons of childhood mortality, usage of the emergency department for mental health issues, validation of liver disease case definitions, and maternal outcomes for incarcerated women. In her current role at CIHI, Laura and her team work to support the analytic capacity of Canada’s western jurisdictions.
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.