Simon Fraser University
Engaging the World

Course Outlines

Spring 2020 - STAT 856 G100

Longitudinal Data Analysis (4)

Class Number: 5231

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 6 – Apr 9, 2020: Tue, Thu, 2:30–4:20 p.m.
    Burnaby

  • Prerequisites:

    STAT 450 or permission of the instructor.

Description

CALENDAR DESCRIPTION:

Methods for the analysis of repeated measures, correlated outcomes and longitudinal data, including unbalanced and incomplete data sets, characteristic of biomedical research are covered. Topics include covariance pattern models, random or mixed-effects models, multilevel models, generalized estimating equations, inference for multistate processes and counting processes, and methods for handling missing data.

COURSE DETAILS:

Outline:

 

  1. Examples of longitudinal studies and approaches to longitudinal analysis.
  2. Repeated Measures ANOVA 
  3. Exploring correlation structures; parametric models for correlation
  4. Contrasting marginal, random effects and transitional models
  5. Random effects and conditional models
  6. Marginal models using generalized estimation equations
  7. Unbalanced and incomplete data
  8. Multilevel models
  9. Missing Data Methods, Imputation, Sensitivity Analysis

Grading

  • Assignments 50%
  • mid-term 30%
  • Class Presentation 20%

Materials

REQUIRED READING:

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

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

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

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS