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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;
- Understand how and why advanced techniques are used in statistical analysis, and the importance of confounder control and effect modification detection;
- Use SPSS for regression modelling of their data;
- Interpret computer output from multiple, repeated-measures, logistic or Cox regression in SPSS or other computer packages;
- Critically evaluate the 'statistical methods' section of a scientific publication.
- Linear regression
- Logs and exponentials (revision)
- Logistic regression
- 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|
|Specified Learning Activities||
|Autonomous Student Learning||
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.
|Description||Timing||Component Scale||% of Final Grade|
|Assignment: Practical assignment||Varies over the Trimester||n/a||Standard conversion grade scale 40%||No||
|Examination: Written examination||2 hour End of Trimester Exam||No||Standard conversion grade scale 40%||No||
|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.
|Dr Ricardo Piper Segurado||Lecturer / Co-Lecturer|