Show/hide contentOpenClose All
Curricular information is subject to change
At the end of this module students will be able to:
• Appreciate the usefulness and limitations of statistical modelling approaches to data analysis;
• Be able to choose an appropriate model in a given analysis situation, including assessing appropriateness and choice of covariates and interaction effects
• Use and interpret statistical software for linear, logistic or Cox regression modelling of their data;
• Present the results of regression models using correct and interpretable tables and graphs
• Critically evaluate the 'statistical methods' section of a scientific publication.
- Linear regression
- Correlation
- Logs and exponentials (revision)
- Logistic regression
- Confounding
- Interaction / effect modification
- Time-to event analyses - life tables and Kaplan-Meier curves
- Cox Proportional Hazards Regression
- Paired and longitudinal analyses with ANOVA
Student Effort Type | Hours |
---|---|
Lectures | 20 |
Tutorial | 4 |
Specified Learning Activities | 20 |
Autonomous Student Learning | 80 |
Total | 124 |
Students should have completed the modules PHPS40010: Fundamentals of Epidemiology, and PHPS40190: Biostatistics 1 or equivalent.
Prior to attending this module students should also have a basic knowledge of the use of SPSS (entering data, defining data properties etc.). Ideally students will bring their own laptops to lectures.
For more information, please, contact the module coordinator.
Resit In | Terminal Exam |
---|---|
Summer | Yes - 2 Hour |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
The assignment is given individualised feedback. There is also general in-class feedback on performance and common areas of weakness and strength.
Name | Role |
---|---|
Mr John Loughrey | Lecturer / Co-Lecturer |
Dr Ricardo Piper Segurado | Lecturer / Co-Lecturer |