Spring 2020 - HSCI 484 D100

Senior Seminar in Population Health Research (3)

Class Number: 2201

Delivery Method: In Person


  • Course Times + Location:

    Tu, Th 2:30 PM – 4:20 PM
    BLU 11660, Burnaby

  • Prerequisites:

    90 units, including HSCI 330 and either STAT 302 or STAT 305.



Scientific research in population health. Developing and evaluating research protocols, taking a general research question and turning it into an analysis plan, carrying out the analysis, and writing up the findings for presentation and publication.


Population health researchers are interested in data-driven evidence-based practices.  This course will introduce students to research methods, analysis and reporting with emphasis on longitudinal and administrative data.  Over the term, we will explore and learn longitudinal study and analysis in different contexts.  Cases will be discussed with examples drawn from the literature and students will learn the longitudinal data as compared with cross-sectional data and administrative data as compared with alternative data sources. Students will learn statistical models and techniques for properly analyzing longitudinal data and interpret results from these analyses.


The educational goals of this course are for using longitudinal data or administrative data, two very common data sources,  for health research and interpret results from analyzing these data. 

By fulfilling the course requirements students will be prepared to:

1.     Examine the strengths and weaknesses of longitudinal data vs cross-sectional data, administrative data vs alternative data courses, understand how to analyze data, implementation challenges and how to interpret results properly.
2.     Learn about statistical models and techniques, including repeated measures ANOVA, mixed-effects models and marginal models, for analyzing longitudinal, or repeated measures, data. 
3.    Focus primarily on appreciation and application of the statistical methods using standard software SAS. 
4.    Models and methods will be illustrated using a set of real data examples in public health, medical and social sciences. 


  • Assignment 50%
  • Mid-term 30%
  • Class presentation 20%



Analysis of Longitudinal Data, 2nd ed. (2013) by Peter Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger, Oxford Statistical Science Series. 

Registrar Notes:

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html