9:00 – 9:30

Introduction to Clinical Data Analytics

9:30 – 10:00

Criteria for causation (relevance of study design)

10:00 – 10:30

Applied Medical Statistics – Worked Examples – INTERSTROKE Analysis with code side by side

10:45 – 11:15

Introduction to the UK Biobank Dataset

11:15 – 11:45

Non-linear methods (Traditional biostats and machine learning)

12:30 – 13:30

Practical R coding (Introduction to R-markdown)

13:30 – 14:00

Creating a “Table 2” in R

14:00 – 14:30

Difference between more than two groups (ANOVA)

14:30 – 15:00

Introduction to plots with ggplot in R

15:00 – 15:30

Missing Data in R

15:30 – 16:00

Imputation in R

16:00 – 16:30

Non-linear methods in R practical