MSA680 Data science for biomedicine Spring 24
This page contains the program of the course: lectures, computer labs, teachers, literature and examination.
Program
The schedule of the course is in TimeEdit.
Exams
Exams from old courses here
Lectures
| Day | Room | Book | Instructor | Content |
|---|---|---|---|---|
| 2024-01-17 | MVF21 | C&L Chapters 1-2 | José Sánchez |
Introduction to course (slides) Introduction to controlled randomised experiments (slides) |
| 2024-01-19 | Pascal | C&L Chapters 3-4 | Gabriel Abreu | Basic designs and randomisation for controlled experiments (slides) |
| 2024-01-24 | MVF21 | C&L Chapters 7-9 | Gabriel Abreu | Hypothesis testing for efficacy, non-inferiority and bio-equivalence (slides) |
| 2024-01-26 | Pascal | C&L Chapter 8 | Gabriel Abreu |
Analysis of continuous data (slides) |
| 2024-01-31 | MVF21 | C&L Chapter 11-12 | Karin Nelander |
Sample size calculation and multiplicity (slides) |
| 2024-02-02 | Pascal | V&M Chapters 1-4 | José Sánchez | Introduction to linear mixed effects models (slides) |
| 2024-02-07 | MVF21 | V&M Chapter 5 | José Sánchez | Estimation for the marginal model (slides) |
| 2024-02-09 | Pascal | V&M Chapter 6 | José Sánchez | Inference for the marginal model (slides) |
| 2024-02-14 | MVF21 | V&M Chapter 7 | José Sánchez | Inference for the random effects (slides) |
| 2024-02-16 | Pascal | V&M Chapter 8 | José Sánchez | Fitting mixed models in SAS and R (slides) |
| 2024-02-21 | MVF21 |
C&L Chapter 10 |
Karin Nelander | Survival analysis (slides) |
| 2022-02-23 | Pascal | Lecture notes | Karin Nelander |
Simulation (slides) |
| 2024-02-28 | MVF21 | Lecture notes/G&H Chapters 11-12 | José Sánchez | Introduction to Bayesian inference and meta-analysis (slides) |
| 2024-03-01 | Pascal | Lecture notes | José Sánchez | Hierarchical models and partial-pooling (lecture notes, Meta-analysis example, Randon example) |
| Exam |
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) |
Sofware
- R https://www.r-project.org/
- RStudio https://www.rstudio.com/
- Stan https://mc-stan.org/
- SAS SAS OnDemand for Academics
Computer labs
| Files | Computer lab sessions | Report hand-in |
| Lab0 | 2024-01-17, 2024-01-24 | No report needed |
| Lab1 | 2024-01-31, 2024-02-07 | 2024-02-09 |
| Lab2 | 2024-02-14, 2024-02-21 | 2024-03-01 |
| Lab3 | 2024-02-21, 2024-02-28 | 2024-03-08 |
| Lab4 (optional) | 2024-03-17 |
Grading
The written exam is worth up 24 points and each computer lab up to 3 points.
- Less than 18 points – fail/U
- 19 to 23 points – pass/G/3
- 24 to 28 points – pass/G/4
- 29 points or more – excellent/VG/5
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.
- 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.