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Faculty of Health and Life Sciences

Applied Statistical Modelling for Health and Life Sciences CPD Course

Dates:  8th, 13th, 15th, 20th and 22nd May 2025 (13:00 - 17:00 UK Time) 

Venue: Synchronous via Zoom 

BOOK NOW!

Early Bird Rate available until 20th March!

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Photo credit: Tara Winstead

About the course

This course provides a broad introduction to statistical modelling for health and life science applications. The fundamental role of the statistician as a problem solver will be emphasised and the different stages of the “problem solving” cycle will be considered.

The course will equip you with the theoretical underpinning and computational skills needed for generalized linear regression modelling of health data using the R statistical software. Real-world case studies drawing on our world-class epidemiological research will be used to help you develop an appreciation of modelling strategy and to give you practical experience of interpreting model findings in the context of real health problems.

Course requirements 

The course requires familiarity with basic statistical concepts and methods (e.g. descriptive statistics and graphs, t-tests). Some knowledge of R would be advantageous. On 8th May the course has built in a half-day preparatory session on R software to support all delegates in achieving the required level of proficiency in the R software environment.

Learning outcomes

  • Formulate health research questions as statistical problems.
  • Learn and be able to implement linear regression, logistic regression and survival analysis methods in R software.
  • Interpret and critically evaluate the results of statistical modelling in the context of a quantitative research question.

After completing this course, you might be interested in exploring the Master in Health Data Science to develop advanced understanding and skills in statistical computing, machine learning and analysis of big data.

External accreditation

CPD points applied for through the Royal College of Physicians.

 

BOOK NOW!

Early Bird Delegate Rate - £1,170 (until 20th March 2025)

Standard Delegate Rate - £1,300 (from 21st March 2025)

Reduction for PhD students/UoE Staff - £800

Delivery dates:

8th, 13th, 15th, 20th & 22nd May 2025 (13:00-17:00 GMT) 

Delivery format

Synchronous delivery via Zoom.

Suitable for Academics, PhDs, industry/NHS, and for those who need to use quantitative models to analyse data to generate evidence or inform policy. This includes researchers and data analysts wanting a practical framework for modern regression modelling of data from clinical trials, or routine health data from electronic health records. 

 

Programme

(*The programme may be subject to minor amendments)

We advise you to make every effort to join all sessions to gain the most out of the course.

Day 1- Pre-course – Introduction to R - 8th May 2025

 Using R Studio to write scripts and run R commands 

  • Different types of objects for storing data  
  • Reading in and organising data, and saving the output 
  • Summarising and visualising data in R 

Day 2 - Linear Regression Modelling - 13th May 2025

FORMAT

TOPIC

DURATION

Lecture I

What is statistical modelling

30 minutes

Lecture II

An introduction to linear regression analysis: model estimation and interpretation

30 minutes

Lecture III

Model assumptions and diagnostics

30 minutes

 

Break

30 minutes

Workshop I

Case study: the Brains for Dementia Research Study

15 minutes

Workshop II

Linear regression analysis in R

60 minutes

 

Break

15 minutes

Workshop III

Interactive discussion and wrapping up

30 minutes

 

Day 3 – Logistic Regression Modelling – 15th May 2025

FORMAT

TOPIC

DURATION

Lecture I

Introduction to statistical modelling of categorical data

30 minutes

Lecture II

Logistic regression analysis: model estimation and interpretation

30 minutes

Lecture III

Model assumptions and diagnostics

30 minutes

 

Break

30 minutes

Workshop I

Case study: the Diabetes prediction dataset

15 minutes

Workshop II

Logistic regression analysis in R

60 minutes

 

Break

15 minutes

Workshop III

Interactive discussion and wrapping up

30 minutes

 

Day 4 - Complex Data Structures and Interaction Modelling – 20th May 2025

FORMAT

TOPIC

DURATION

Lecture I

Complex data structures in health research

15 minutes

Lecture II

Modelling statistical interactions

30 minutes

Lecture III

An introduction to hierarchical regression models

45 minutes

 

Break  

30 minutes

Workshop I

Case study: longitudinal cognitive and clinical assessment data from the Brains for Dementia Research Study

15 minutes

Workshop II

Mixed effects models in R

60 minutes

 

Break

15 minutes

Workshop III

Interactive discussion and wrapping up

30 minutes

 

Day 5 – Survival Analysis - 22nd May 2025

FORMAT

TOPIC

DURATION

Lecture I

Time-to-event data in health research

30 minutes

Lecture II

An introduction to Cox regression analysis: model estimation and interpretation

30 minutes

Lecture III

Model assumptions and diagnostics

30 minutes

 

Break

30 minutes

Workshop I

Case study: the Framingham Heart Study

15 minutes

Workshop II

Survival analysis in R

60 minutes

 

Break

15 minutes

Workshop III

Interactive discussion and wrapping up

30 minutes

 

Whether you study on-campus, virtually, or via a blended learning programme, you'll be supported by the University of Exeter's world-class faculty with wide-ranging opportunities to develop interdisciplinary and vocational skills. 

Learn about our Master of Health Data Science.

 

 

Speakers

Led by University of Exeter Professor William Henley and guest lecturer, Dr Adam Streeter (Münster, Germany) alongside a team of invited experts.