Course Number : 667
Course Title : Advanced biostatistics for clinical research
Course Credit : 3 credits
Prerequisite : BIOMED 642 and 643 or equivalent and permission of instructor
Placement in Curriculum : Winter Semester (second semester)
Course Description : The course will cover through lectures, discussions, and a group analysis current methods for analyzing longitudinal and clustered, clinical data. Topic areas covered will include multi-level, multi-state, multi-process, and structural equation models.
Course Objectives : In this course, students will:
- Learn statistical methods for analyzing longitudinal and clustered data
- Present journal articles that have used the methods
- Propose studies that might apply the methods within their clinical specialties
- Conduct an analysis as a group of a clinical dataset
Learning Outcomes
At the conclusion of the course students will be able to:
- Understand the clinical literature using longitudinal or clustered designs
- Include these designs within their own research studies
- Know how to participate in the analysis of a clinical dataset
- Learn how to write up the results of longitudinal analyses
Topical Outline :
General Sessions
Discrete time logistic regression |
Modeling time dependent explanatory variables |
Competing risk models |
Repeated measures analysis |
Multi-state transition models |
Introduction to multi-level models |
Multi-level models for normally distributed data |
Multi-level models for binary data |
Multi-level models for multinomial and ordinal data |
Multiple membership models |
Overview of multi-process models |
Modeling possibilities using multi-process models |
Introduction to structural equation models |
Growth modeling with continuous outcomes |
Growth modeling with categorical outcomes |
Cross-sectional mixture modeling |
Longitudinal mixture modeling |
Multi-level latent variable models |
Teaching Methods
- Lectures on statistical methods
- Student presentations of journal articles
- Student presentations of study designs within their specialty areas
- Analysis with group discussions of a clinical dataset
- Write-up of the results of the statistical analysis
Required Reading :
Students will be given one or two articles per class session to read and discuss in class.
Learning Experiences :
Lecture, group discussions, individual presentations, data analysis, manuscript preparation
Evaluation :
Journal article presentations 25%
Proposed study designs 25%
Data analysis and write-up 50%