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# Survival Analysis - MAT00018H

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• Department: Mathematics
• Module co-ordinator: Dr. Agostino Nobile
• Credit value: 10 credits
• Credit level: H
• Academic year of delivery: 2020-21

## Related modules

• None

### Prohibited combinations

Pre-requisites for Natural Sciences students: Statistics Option MAT00033I.

## Module will run

Occurrence Teaching cycle
A Autumn Term 2020-21

## Module aims

To present a statistical methodology for the analysis of survival time data stemming from medical experiments where patients are subjected to a treatment.

## Module learning outcomes

At the end of this module you should be able to:

• Provide descriptive statistics and graphical summaries of information contained in data from survival experiments in different types of studies
• Use estimation and hypothesis testing for inference
• Use proportional hazards regression techniques to make inferences about the possible relationship between survival time and potential risk factors.

## Module content

Syllabus

• Censoring and truncation.
• Basic quantifiers of survival: survival, hazard and cumulative hazard functions.
• Non-parametric estimation of the survival and cumulative hazard functions.
• Log-rank test.
• Parametric models for survival data: exponential, Weibull, log-normal, log-logistic.
• Accelerated Failure time model.
• Proportional Hazards Property.
• Cox Proportional Hazards Model.
• Variable and Model selection.
• Checking the Proportional Hazards assumption.
• Stratified Cox PH model.
• Cox-Snell, Martingale and Schoenfeld residuals.

## Assessment

Task Length % of module mark
Online Exam - 24 hrs (Centrally scheduled)
Survival Analysis
N/A 100

None

### Reassessment

Task Length % of module mark
Online Exam - 24 hrs (Centrally scheduled)
Survival Analysis
N/A 100

## Module feedback

Current Department policy on feedback is available in the undergraduate student handbook. Coursework and examinations will be marked and returned in accordance with this policy.