• Class Number 4426
• Term Code 3130
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• Robert Clark
• LECTURER
• Robert Clark
• Class Dates
• Class Start Date 22/02/2021
• Class End Date 28/05/2021
• Census Date 31/03/2021
• Last Date to Enrol 01/03/2021
SELT Survey Results

Survival Models (STAT3032)

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. Explain the concept of survival models;
2. Describe the estimation procedures for lifetime distributions;
3. Understand and describe 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. Describe how to estimate transition intensities depending on age, exactly or using the census approximation; and,
6. Communicate 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 an intermediate level of programming with R, including model fitting, graphical analysis and forecasting. In the lectures and weekly computer labs, 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.

## Examination Material or equipment

The mid-semester and final exam will be administered online and be open book. Examination materials and conditions will be noticed to all students via Wattle and the examination office.

## 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 (online and local tutorials)
• lecturer consultations (online)

## 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.

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/

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

STAT3032/STAT4072/STAT7042/STAT8003 will be taught jointly. There may be some material which is only relevant to some of these codes. This will be clearly identified during the lecture and/or tutorial.

## Class Schedule

Week/Session Summary of Activities Assessment
1 Data Types, Introduction to Survival Models
2 Introduction to Survival Models
3 Estimation Methods, Kaplan-Meier Estimation
4 Kaplan-Meier Estimation (continued) / Nelson Aalen Estimation
5 Kaplan-Meier (continued) / Nelson Aalen Estimation (continued) / Cox Regression Assignment 1 due Tuesday of week 5 (23/3/2021)
6 Cox Regression (continued) Feedback of Assignment 1 by 1/4. Mid Semester Exam in either week 6 or week 7.
7 Two State Models / Multistate Models Mid Semester Exam in either week 6 or week 7
8 Multi State Models (continued), Mortality Graduation, Smoothing and Forecasting
9 Mortality Graduation, Smoothing and Forecasting (continued)
10 Mortality Graduation, Smoothing and Forecasting (continued) Assignment 2 due Friday of week 10 (14/5/2021)
11 Mortality Graduating, Smoothing and Forecasting (continued)
12 Introduction to Census Method. Mortality, Selection and Standardisation Feedback on Assignment 2 by 28/5

## Tutorial Registration

Tutorials will be available on campus, live through scheduled zoom sessions, and as pre-recorded videos. Information regarding enrolments for these options will be provided on

Wattle during O-week , prior to the start of the semester.

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 10 % 23/03/2021 01/04/2021 1-2
Mid Semester Exam 25 % 29/03/2021 07/05/2021 1-6
Assignment 2 10 % 14/05/2021 28/05/2021 1-2
Final Exam 55 % 03/06/2021 01/07/2021 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. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

## 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.

## Participation

Lectures will be recorded through Echo360. Consultations will be live through Zoom. Tutorials will be available on campus, live through scheduled Zoom sessions and as prerecorded videos. Information regarding enrolments for these options will be provided on Wattle during O-week prior to the start of the semester.

## Examination(s)

The mid semester examination will be two hours long. The final examination will be three hours long. Both exams will be open book and administered online. Students will be notified regarding examination materials and conditions via Wattle and the examination office.

Centrally scheduled examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information.

Value: 10 %
Due Date: 23/03/2021
Return of Assessment: 01/04/2021
Learning Outcomes: 1-2

Assignment 1

Assignment 1 will be made available on Wattle by 9 March. It will involve obtaining suitable life table data and a continuous time survival dataset, performing exploratory data analysis using R, and writing a report.

Value: 25 %
Due Date: 29/03/2021
Return of Assessment: 07/05/2021
Learning Outcomes: 1-6

Mid Semester Exam

The mid-semester exam will be a two hour open book exam administered online. It will cover the week sessions 1 to 5 and will be in approximately Week 6 or Week 7. Students will be notified regarding examination materials and conditions via Wattle and the examination office.

Value: 10 %
Due Date: 14/05/2021
Return of Assessment: 28/05/2021
Learning Outcomes: 1-2

Assignment 2

Assignment 2 will be made available on Wattle by 30 April. It will include data analysis conducted in the R statistical environment and writing a report.

Value: 55 %
Due Date: 03/06/2021
Return of Assessment: 01/07/2021
Learning Outcomes: 1-6

Final Exam

The final exam will be a three-hour open book exam conducted online. It will cover the entire course. Students will be notified regarding examination materials and conditions via Wattle and the examination office.

Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.

The ANU commits to assisting all members of our community to 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 be familiar with the academic integrity principle and Academic Misconduct Rule, 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.

## 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) submission must be through Turnitin.

## Hardcopy Submission

There is no hardcopy submission in the course.

## Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

• Late submission permitted. 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.

## Returning Assignments

Assignments will be returned to students online.

## Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted 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.

## Resubmission of Assignments

It will not be possible to resubmit assignments.

## 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.
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.

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).

## Convener

 Robert Clark 0261003320 robert.clark@anu.edu.au

### Research Interests

sample surveys design and analysis, statistical ecology, latent variable models and applied statistics.

### Robert Clark

 Thursday 16:00 18:00 Thursday 16:00 18:00

## Instructor

 Robert Clark 0261003320 robert.clark@anu.edu.au

### Robert Clark

 Thursday 16:00 18:00 Thursday 16:00 18:00