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Unit of study_

BSTA5009: Survival Analysis

Semester 1, 2020 [Online] - Camperdown/Darlington, Sydney

The aim of this unit is to enable students to analyse data from studies in which individuals are followed up until a particular event occurs, e.g. death, cure, relapse, making use of follow-up data also for those who do not experience the event, with proper attention to underlying assumptions and a major emphasis on the practical interpretation and communication of results. The content covered in this unit includes: Kaplan-Meier life tables; logrank test to compare two or more groups; Cox's proportional hazards regression model; checking the proportional hazards assumption; time-dependent covariates; multiple or recurrent events; sample size calculations for survival studies.

Unit details and rules

Unit code BSTA5009
Academic unit Public Health
Credit points 6
Prohibitions
? 
None
Prerequisites
? 
BSTA5007
Corequisites
? 
None
Available to study abroad and exchange students

No

Teaching staff

Coordinator Patrick Kelly (Public Health), p.kelly@sydney.edu.au
Type Description Weight Due Length
Assignment Assignment 1
This assessment covers modules 1 and 2
30% Week 05 3-4 pages
Outcomes assessed: LO1 LO2 LO3
Assignment Assignment 2
This assessment covers modules 3 and 4
40% Week 09 4-6 pages
Outcomes assessed: LO1 LO2 LO3
Assignment Assignment 3
This assessment covers modules 5 to 7.
30% Week 13 3-4 pages
Outcomes assessed: LO4 LO5 LO6 LO7

Assessment summary

Assessment will be 3 written assignments worth 30%, 40% and 30% each, to be made available after the first week of the modules to be covered, and to be completed  within approximately 4 weeks. These assignments will be posted on the eLearning site together with an online Announcement broadcasting their availability. 

Assessment criteria

Grade

Mark Range

Description

AF

Absent fail

Range from 0 to 49

To be awarded to students who fail to demonstrate the learning outcomes for the unit at an acceptable standard through failure to submit or attend compulsory assessment tasks or to attend classes to the required level. In cases where a student receives some marks but fails the unit through failure to attend or submit a compulsory task, the mark entered shall be the marks awarded by the faculty up to a maximum of 49. This grade should not be used in cases where a student attempts all assessment tasks but fails to achieve a mandated minimum standard in one or more task. In such cases a Fail (FA) grade and a mark less than 50 should be awarded.

FA

Fail

Range from 0 to less than 50

To be awarded to students who, in their performance in assessment tasks, fail to demonstrate the learning outcomes for the unit at an acceptable standard established by the faculty. This grade, with corresponding mark, should also be used in cases where a student fails to achieve a mandated standard in a compulsory assessment, thereby failing to demonstrate the learning outcomes to a satisfactory standard.

PS

Pass

Range from 50 to less than 65

To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an acceptable standard

CR

Credit

Range from 65 to less than 75

To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a good standard

D

Distinction

Range from 75 to less than 85

To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a very high standard

HD

High distinction

Range from 85 to 100 inclusive

To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an exceptional standard

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Module 1: The nature of survival data, including censoring; the survival (or survivorship) function: definition and estimation via the Kaplan-Meier curve; the stset command in Stata; Kaplan-Meier estimate of the survival (or survivorship) function: confidence intervals and hypothesis testing. Individual study (20 hr) LO1 LO2
Week 03 Module 2: The density, survival, hazard and cumulative hazard functions; the Nelson-Aalen estimate of the cumulative hazard function; Definition of the proportional hazards model; construction of the partial likelihood for the Cox model; the treatment of tied failure times; hypothesis testing on the coefficients, using Wald and partial likelihood ratio tests. Individual study (20 hr) LO1 LO2
Week 05 Module 3: For the Cox PH model: hypothesis testing on the coefficients, continued; estimation of the baseline functions S0(t) and H0(t), and their adjustment for covariate values; the effect of a change in scale and origin of units of measurement of covariates. Individual study (20 hr) LO3
Week 07 Module 4: Model diagnostics for the Cox PH model; the stratified Cox model. Individual study (20 hr) LO3
Week 09 Module 5: Time-dependent covariates in the Cox model; parametric survival time models, in particular the accelerated failure time model, with an exponential and Weibull distribution; discrete-time logistic model. Individual study (20 hr) LO3 LO4
Week 11 Module 6: Correlated survival data; clustered survival data; recurrent events models. Individual study (20 hr) LO5
Week 13 Module 7: Sample size determination for comparing two response rates and two survival distributions; good practice for the display of survival analysis results in scientific publications. Individual study (10 hr) LO6 LO7

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Understand the nature of survival data
  • LO2. Summarise and display survival data using nonparametric methods
  • LO3. Analyse survival data using the Cox proportional hazards model, including time-dependent covariates
  • LO4. Analyse survival data using parametric models
  • LO5. Analyse data using multi-event models
  • LO6. Determine sample size for simple survival analysis
  • LO7. Produce appropriate displays for publication

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered

Disclaimer

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