Advanced Statistical Analysis

The course will cover a range of more advanced statistical techniques used in healthcare. In particular:

• Survival analysis.
• Generalised linear models.
• Methods for handling missing data with a focus on multiple imputation.
• Causal methods such as directed acyclic graphs and propensity scores.
• Bootstrapping and related methods.

The course assumes familiarity with descriptive statistics, linear and logistic regression.

Module Code

CHME0029

UCL Credits

15

Module Organisers

Dr Henry Potts & Dr Michalis Katsoulis. Please direct queries to courses-IHI@ucl.ac.uk

Course Length

9 Weeks

Course Dates

12:00-17:00

04 May – 02 July with

SYNC DAYS

02, 03, 04 June

The assignment is due on 05 July, 5pm.

Content

Key topics covered by this module include:

• Sampling error
• Statistical tests, such as:
  • linear regression
  • logistic regression
  • time-to-event analysis
  • multiple regression
• Core ideas of statistical modelling
• Use of Stata, a statistical software package

Teaching and learning methods

Blended learning: web-based distance learning in the UCL Virtual Learning Environment plus a 3-day face-to-face teaching session (depending upon social distancing regulations)

Assessment

Summative assessment: Written report worth 100% of the overall module mark.