MSA680 Data science for biomedicine Spring 22
This page contains the program of the course: lectures, and computer labs. Other information, such as learning outcomes, teachers, literature and examination, are in a separate course PM.
Program
The schedule of the course is in TimeEdit.
Exams
Exams from old courses here
Lectures
| Day | Room | Book | Instructor | Content |
|---|---|---|---|---|
| 2022-01-19 | MVF21 | C&L Chapters 1-2 | Yevgen Ryeznik |
Introduction to controlled randomised experiments (slides) Introduction slides |
| 2022-01-21 | EC | C&L Chapters 3-4 | Yevgen Ryeznik | Basic designs and randomisation for controlled experiments (slides) |
| 2022-01-26 | MVF21 | C&L Chapters 7-9 | Yevgen Ryeznik | Hypothesis testing for efficacy, non-inferiority and bio-equivalence (slides) |
| 2022-01-28 | EA* | C&L Chapter 10 | Karin Nelander |
Survival analysis (slides) |
| 2022-02-02 | MVF21 | C&L Chapter 11 | Karin Nelander | Sample size calculation and multiplicity (slides) |
| 2022-02-04 | Pascal* | Harrell Chapter 5 | Karin Nelander |
Bootstrap and simulation (slides) |
| 2022-02-09 | MVF21 | V&M Chapters 1-4 | José Sánchez | Introduction to linear mixed effects models (slides) |
| 2022-02-11 | Pascal* | V&M Chapter 5 | José Sánchez | Estimation for the marginal model (slides) |
| 2022-02-16 | MVF21 | V&M Chapter 6 | José Sánchez | Inference for the marginal model (slides) |
| 2022-02-18 | Pascal* | V&M Chapter 7 | José Sánchez | Inference for the random effects (slides) |
| 2022-02-23 | MVF21 | V&M Chapter 8 | José Sánchez | Fitting mixed models (in SAS) (slides, code) |
| 2022-02-25 | Pascal* | G&H Chapters 11-12 | José Sánchez | Introduction to Bayesian hierarchical models (meta-analysis) |
| 2022-03-02 | MVF21 | José Sánchez | Hierarchical models and partial-pooling | |
| 2022-03-04 | Pascal* | José Sánchez | Fitting hierarchical models (in Stan and R) Material |
Recommended reading
| Book/Chapter | Section |
|---|---|
| V&M 1-5 | Whole chapter |
| V&M 6 | 6.1 to 6.3.3 |
| V&M 7 | 7.1-7.7 |
| V&M 8 | Whole chapter |
| C&L 1, 2, 3, 4, 7, 8, 9 | Whole chapter |
| C&L 10 |
10.1-10.3 10.4 (Not the part on time dependent covariates) |
| C&L 11 |
11.1-11.3 |
| C&L 12 |
12.6 (Not composite index and subgroup analysis) |
| Harrell 5 |
5.1-5.2 |
Sofware
- R https://www.r-project.org/
- RStudio https://www.rstudio.com/
- SAS SAS OnDemand for Academics
- Stan https://mc-stan.org/
Computer labs
| Files | Computer lab sessions | Report hand-in |
| Lab1 | 2022-01-19 to 2022-01-26 | No report needed |
| Lab2 | 2022-02-02 to 2022-02-16 | 2022-02-18 |
| Lab3 | 2022-02-23 to 2022-03-02 | 2022-03-04 |
Contacts
Reference literature
- Design and analysis of Clinical Trials: Concepts and Methodologies, Shein-Chung Chow and Jen-Pei Liu, Third Edition, Wiley. Available as e-book at Chalmers library.
- Regression Modeling Strategies (With Applications to Linear Models, Logistic Regression, and Survival Analysis), Frank Harrell Jr, Springer Verlag, New York. Available as e-book at Chalmers library.
- Linear mixed models for longitudinal data, Geert Verbeke and Geert Molenberghs, Springer Verlag, New York.
- Data analysis using regression and multilevel/hierarchical models, Adrew Gelman and Jennifer Hill, Cambridge University Press.
Course summary:
| Date | Details | Due |
|---|---|---|