- Class Number 3231
- Term Code 3030
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Robert Clark
- Robert Clark
- Class Dates
- Class Start Date 24/02/2020
- Class End Date 05/06/2020
- Census Date 08/05/2020
- Last Date to Enrol 02/03/2020
This course introduces survival models and discusses their estimation and their application to mortality. Topics covered will include: 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.
Upon successful completion, students will have the knowledge and skills to:
- Explain the concept of survival models;
- Describe in detail the estimation procedures for lifetime distributions;
- Implement complex statistical models of transfer between multiple states, including processes with single or multiple decrements, and derive relationships between probabilities of transfer and transition intensities;
- Derive maximum likelihood estimators for the transition intensities in complex models of transfers between states with piecewise constant transition intensities;
- Comprehensively describe how to estimate transition intensities depending on age, exactly or using the census approximation; and,
- 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.
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
A non-programmable calculator, one A4-size paper with notes on both sizes and paper-based dictionary (no approval needed; dictionary can be English language or a translation dictionary; all notes must be removed) are allowed in the mid-semester and final exam.
Lecture notes and other course materials will be updated weekly with the progress of this course on Wattle.
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
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.
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.
This course will be taught alongside STAT4072/STAT7042/STAT8003. There will be some material in this course which may not be relevant to STAT3032. This will be clearly identified during the lecture and/or tutorial.
|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 Friday of week 5 (27/3/2020)|
|6||Cox Regression (continued)||Mid Semester Exam (approximately)|
|7||Two State Models / Multistate Models|
|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 (15/5/2020)|
|11||Mortality Graduating, Smoothing and Forecasting (continued)|
|12||Introduction to Census Method. Mortality, Selection and Standardisation|
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 task||Value||Due Date||Return of assessment||Learning Outcomes|
|Assignment 1||8 %||27/03/2020||03/04/2020||1-2|
|Mid Semester Exam||30 %||*||*||1-6|
|Assignment 2||8 %||15/05/2020||22/05/2020||1-2|
|Final Exam||54 %||*||*||1-6|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
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:
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.
The mid semester examination will be 1.5 hour long with 15 minutes reading time. The final examination will be 3 hours long with a 15 minutes reading time. One A4-size paper with notes on both sizes and paper-based dictionary (no approval needed; dictionary can be English language or a translation dictionary; all notes must be removed) are allowed for both examinations.
Assessment Task 1
Learning Outcomes: 1-2
Assignment 1 will be made available on Wattle by 13 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. Assignment 1 is optional and redeemable.
Assessment Task 2
Learning Outcomes: 1-6
Mid Semester Exam
Closed-book exam will cover the week sessions 1 to 5 and will be in approximately Week 6 or Week 7. The mid-semester examination will be 1.5 hours 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; dictionary can be English language or a translation dictionary; all notes must be removed) are allowed. The mid-semester exam is optional and redeemable (mark will be replaced by final exam mark).
Assessment Task 3
Learning Outcomes: 1-2
Assignment 2 will be made available on Wattle by 1 May. It will involve conducting analyses on the data obtained in your Assignment 1 using the R statistical environment and writing a report. Assignment 2 is optional and redeemable.
Assessment Task 4
Learning Outcomes: 1-6
The final exam will be a three-hour closed-book exam (plus 15 minutes reading time). It will cover the entire course. A non-programmable calculator, one A4-size paper with notes on both sizes and paper-based dictionary (no approval needed; dictionary can be English language or a translation dictionary; all notes must be removed) are allowed.
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.
The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.
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.
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.
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.
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.
Assignments will be returned to students in their enrolled computer lab.
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.
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).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
His research interests are in sample surveys design and analysis, statistical ecology, latent variable models and applied statistics.