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Introduction to Survival Analysis: Online - (2 days)
Survival analysis is used to find out the time it takes for an event of interest to occur (e.g., death, birth, recidivism). This course is designed as an introduction to survival analysis.
Instructor
Dr Joanna Dipnall is an applied statistician with particular interests in the advanced statistical methods and machine and deep learning techniques. She completed her Honours in Econometrics with Monash University and PhD with IMPACT SRC, School of Medicine, Deakin University. Joanna works extensively with registry and linked medical data and collaborates extensively with the Faculty of IT at Monash to supervise Masters and PhD students to integrate AI within health research. Joanna teaches within the Monash Biostatistics Unit and is the Unit Coordinator for the Monash Masters of Health Data Analytics course. Joanna has taught advanced statistical methods for many years at universities and for ACSPRI.
Course Level
Survival analysis is used to find out the time it takes for an event of interest to occur (e.g., death, birth, recidivism). It is used in a variety of fields such as cancer studies to investigate time to death, criminology studies to investigate the time until re-offending, engineering studies for “failure-time analysis” or time until a product fails.
Survival analysis can be used to determine the probability that a participant survives to a set number of years; to evaluate if there are differences in survival between key groups (e.g., drug versus placebo); or even what factors affect participants' chances of survival.
Competing risks analysis is a form of survival analysis that takes into account competing events that may influence survival rates (e.g., death).
Discussion of some of the uses of survival analysis in publications will be discussed at the end of the course.
This course will be offered online via Zoom And will run to the following timetable:
- 10.30am - 11.30am: Instructional session
- 12.30pm - 2.00pm: Instructional session
- 3.00pm - 4.30pm: Exercises and discussion
Please note: Courses will run on Australian Eastern Standard Time (GMT +10)
This course is broken up into the following sections:
Part I: Overview of Survival Analysis
Part II: Kaplan Meyer Curves and Log Rank Tests
Part III: Cox Proportional Hazard Regression
Part IV: Competing Risks Regression
Part V: Survival Analysis in Publications
Participants will be given time to do some exercises on their own to practice what they have learned.
Exercises and solutions will be provided in Stata, R and Python software.
This course assumes that participants have:
(1) Sound familiarity with at least one of the three software packages Stata, R and/or Python.
(2) sufficient understanding of statistics to be able to comprehend the material covered in the course outline, such as a basic grounding in multiple regression (e.g., linear, logistic, Poisson).
(3) access to either Stata, R and/or Python.
(4) some experience in using Microsoft Word and Excel or their equivalent.
(5) experience using a text editor such as Notepad.
Course notes will be supplied. Please include a shipping address when you enrol. Your notes will be express posted to this address.
No specific references are suggested but a number will be supplied with the notes handed out for the course.