• Class Number 3144
  • Term Code 2930
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • AsPr Hanlin Shang
  • LECTURER
    • AsPr Hanlin Shang
  • Class Dates
  • Class Start Date 25/02/2019
  • Class End Date 31/05/2019
  • Census Date 31/03/2019
  • Last Date to Enrol 04/03/2019
SELT Survey Results

This course introduces survival models and discusses their rationale, their estimation and their application to mortality. Topics covered will include: an introduction to the life table; survival models; estimation procedures for lifetime distributions; statistical models of transfers between multiple states; maximum likelihood estimation of transition intensities for such models; binomial model of mortality including estimation and comparison with multiple state models; exposed to risk and methods for smoothing crude mortality rate data.     

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Communicate the concept of survival models.
  2. Communicate in detail the estimation procedures for lifetime distributions.
  3. Implement statistical models of transfer between multiple states, including processes with single or multiple decrements, and derive relationships between probabilities of transfer and transition intensities.
  4. Derive maximum likelihood estimators for the transition intensities in models of transfers between states with piecewise constant transition intensities.
  5. Comprehensively describe how to estimate transition intensities depending on age, exactly or using the census approximation.
  6. Communicate in detail how to test crude estimates for consistency with a standard table or a set of graduated estimates, and describe the process of graduation

Research-Led Teaching

This course involves intermediate level of programming with R. In the lectures and tutorials, we will use real-life datasets to demonstrate the applications of Survival Models in R. Apart from that, additional research articles including journal publications will be provided. Those articles are good examples of how to use appropriate techniques of Survival Models to analyse and solve research questions step-by-step.


Required Resources

Lecture notes and other course materials will be updated weekly with the progress of this course on Wattle.

Staff Feedback

Students will be given feedback in the following forms in this course:

  • Tutorial solutions and discussions
  • Tutorial and lecturer consultations
  • Mid-semester exam solutions and return of paper

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Other Information

Scaling

Your final mark for the course will be based on the raw marks allocated for each assignment or examination. However, your final mark may not be the same number as produced by that formula, as marks may be scaled. Any scaling applied will preserve the rank order of raw marks (i.e. if your raw mark exceeds that of another student, then your scaled mark will exceed or equal the scaled mark of that student), and may be either up or down

Technology,Software and Equipment

This course involves intermediate level of programming with R, which is a powerful and free statistical package widely used by industrial professionals and academics.

 Co-Teaching

This course will be taught alongside STAT4072/STAT7042/STAT3032. There will be some material in this course which may not be relevant to STAT8003. This will be clearly identified during the lecture and/or tutorial.

 Support for Students

The University offers a number of support services for students. Information on these is available online from http://students.anu.edu.au/studentlife/

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction to Survival Models, Week 1 Notes
2 Introduction to Survival Models, Week 2 Notes/ Tute 2
3 Estimation Methods, Week 3 Notes/ Tute 3
4 Kaplan-Meier Estimation, Week 4 Notes/ Tute 4
5 Kaplan-Meier/ Nelson Aalen Estimation, Week 5 Notes/ Tute 5 Online quiz
6 Cox Regression, Week 6 Notes/ Tute 6 Mid Semester Exam
7 Two State Models, Week 7 Notes/ Tute 7
8 Multi State Models, Week 8 Notes/ Tute 8
9 Graduation and Smoothing, Week 9 Notes/ Tute 9
10 Graduation and Smoothing, Week 10 Notes/ Tute 10
11 Methods for Graduating and Smoothing, Week 11 Notes/ Tute 11
12 Introduction to Census Method. Mortality, Selection and Standardisation, Week 12 Notes/ Tute 12

Tutorial Registration

Tutorial signup for this course will be done via the Wattle website. Detailed information about signup times will be provided on Wattle or during your first lecture. When tutorials are available for enrolment, follow these steps:

1.      Log on to Wattle, and go to the course site.


2.      Click on the link “Tutorial enrolment”.

3.      On the right of the screen, click on the tab “Become Member of ……” for the tutorial class you wish to enter.

4.      Confirm your choice.

If you need to change your enrolment, you will be able to do so by clicking on the tab “Leave group…” and then re-enrol in another group. You will not be able to enrol in groups that have reached their maximum number. Please note that enrolment in ISIS must be finalised for you to have access to Wattle.

 

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Online Quiz 0 % 29/03/2019 29/03/2019 1-2
Mid Semester Exam 20 % 01/04/2019 17/05/2019 1-2
Final Exam 80 % 06/06/2019 04/07/2019 1-6

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Assessment Task 1

Value: 0 %
Due Date: 29/03/2019
Return of Assessment: 29/03/2019
Learning Outcomes: 1-2

Online Quiz

An online quiz will be made available on Wattle between 25-29 March. It has zero weighting and will be used as preparation for the mid-semester exam. You will have 1 hour to complete the quiz from when you first open the quiz. Quiz answers will be available immediately after you complete the quiz.

Assessment Task 2

Value: 20 %
Due Date: 01/04/2019
Return of Assessment: 17/05/2019
Learning Outcomes: 1-2

Mid Semester Exam

Close-book exam will cover the week sessions 1 to 6.

Mid-semester exams are redeemable and optional for this course. No deferred mid- semester examinations will be offered, instead the weighting will be moved to the final exam.

 The mid semester examination will be 1.5 hour long with 15 minutes reading time.? A non-programmable calculator, one A4-size paper with notes on both sizes and paper-based dictionary (no approval needed but all notes must be removed) are allowed for both examinations.

Assessment Task 3

Value: 80 %
Due Date: 06/06/2019
Return of Assessment: 04/07/2019
Learning Outcomes: 1-6

Final Exam

Three-hour close-book exam will cover the entire course.

The final examination will be 3 hours long with a 15 minutes reading time. A non-programmable calculator, one A4-size paper with notes on both sizes and paper-based dictionary (no approval needed but all notes must be removed) are allowed for both examinations.

 

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) as submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded.

OR

Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

AsPr Hanlin Shang
u5506744@anu.edu.au

Research Interests


His research interests are in the field of Model Selection, Robust Statistics and Spatial Statistics. He has recently graduated with a PhD degree in Statistics from RSFAS.

AsPr Hanlin Shang

Wednesday 16:00 17:00
Wednesday 16:00 17:00
AsPr Hanlin Shang
6125 0535
hanlin.shang@anu.edu.au

Research Interests


AsPr Hanlin Shang

Wednesday 16:00 17:00
Wednesday 16:00 17:00

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