PHDA 05 - Longitudinal Analysis and Multi-level Modeling of Population Health Data
"The courses I found to be of greatest benefit to me and my work were PHDA-01 (Working with Administrative Data) and PHDA-05 (Longitudinal Analysis and Multi-level Modeling of Population Health Data). These courses provided practical skills that I find I apply regularly to my job, and made me much more comfortable with using data analytic programs like SAS."
Sarah Costa, Health Economist, Canadian Centre for Applied Research in Cancer Control, BC Cancer Agency
Next course delivery: Jan to April 2019
This course is now available to individuals residing outside of Canada. Please contact Program Coordinator, Maxine Reitsma at firstname.lastname@example.org or 250-721-8481 for more information.
This course will provide you with an introduction to—and hands-on experience 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: Shayesteh Jahanfar
Shayesteh Jahanfar is a reproductive epidemiologist with 21 years of teaching and research experience. She is an analytical consultant, an epidemiologist and an assistant professor at Central Michigan supporting health researchers to gain analytical and study design skills. She is a clinician, has two PhDs in Obstetrics and Gynecology (New South Wales University, Australia) and in Epidemiology and Health Care (University of British Columbia, Canada). Her research interests ranges from maternal-child health, domestic violence, endocrinology, family planning, twin studies and reproductive health. She has worked in Australia, Malaysia, Canada and United States teaching both undergraduate and graduate students. She currently teaches epidemiology, biostatistics, and research methods, both online and in traditional settings. She is passionate about learning techniques that makes statistical concepts easier to understand.
This course is offered in partnership with the Division of Continuing Studies and Department of Geography at the University of Victoria.