140.754.41
Advanced Methods in Biostatistics IV

Discontinued

Location
Internet
Term
4th Term
Department
Biostatistics
Credit(s)
4
Academic Year
2024 - 2025
Instruction Method
Synchronous Online
Class Time(s)
Tu, Th, 10:30 - 11:50am
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Hongkai Ji
Contact Name
Hongkai Ji
Frequency Schedule
Every Year
Prerequisite

140.751-753

Description
Extends topics in 140.753 to encompass generalized linear mixed effects models. Introduces expectation-maximization and Markov Chain Monte Carlo. Introduces functional data analysis. Includes foundational topics: linear mixed model, generalized linear mixed model, EM, MCMC, models for longitudinal data, and functional data analysis. Emphasizes both rigorous methodological development and practical data analytic strategies. Discusses the role of quantitative methods and sciences in public health, including how to use them to describe and assess population health, and the critical importance of evidence in advancing public health knowledge.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Explain the role of quantitative methods and sciences and critical importance of evidence in public health
  2. Apply quantitative methods to public health and scientific problems
  3. Extend linear model and generalized linear model to account for clustering and correlation using random effects
  4. Construct, fit and interpret different types of linear mixed model (LMM) and generalized linear mixed model (GLMM) in the context of scientific and public health applications
  5. Apply foundational concepts of probability theory and statistical inference in the context of LMM and GLMM models
  6. Describe the relationship and differences between LMM and GLMM
  7. Conduct statistical inference in these models
  8. Develop and apply Expectation-Maximization (EM) and Markov Chain Monte Carlo (MCMC) algorithms
  9. Solve prediction problems
  10. Produce a complete data analysis to answer a targeted scientific or public health question
Methods of Assessment
This course is evaluated as follows:
  • 60% Homework
  • 40% Final Exam
Instructor Consent
No consent required
Special Comments

Please note: This is the virtual/online section of a course that is also offered onsite. Students will need to commit to the modality for which they register.