Statistical modelling of time-to-event data using survival analysis: an introduction for animal behaviourists, ecologists and evolutionary biologists (TTED01)
21st January 2019 - 25th January 2019£275.00 - £510.00
Survival analysis is a set of statistical methods initially designed to analyse data giving the times at which individuals die, and assess the effect that different predictor variables have on the rate of death. However, its applications are much broader than this: it can be used to analyse any time-to-event data. Ecologists and evolutionary biologists often encounter data of this kind. Often factors influencing survival itself will be of interest. But there are many other cases, e.g. what factors influence the time of first breeding? Or the time taken to reach maturity? Animal behaviourists too will encounter this type of data frequently, e.g. what factors influence the time it takes to learn a novel behaviour pattern? Or the time to respond to a stimulus? etc. And yet the techniques of survival analysis are not generally well known by researchers in these disciplines.
In this course, you will learn how to apply survival analysis models to quantify the effect that predictor variables (continuous or discrete) have on the rate at which events occur, and how to test hypotheses about these effects. We will focus on a flexible modelling technique called the Cox proportional hazards model, which makes minimal assumptions about the underlying probability distributions. You will learn how to fit and interpret these models, how to evaluate its assumptions, and how to extend it to model time dependent variables, random effects, multistate models and competing risks models.
This course would be suitable for participants who have a good understanding of the basic theory
underlying multiple regression/linear models and know how to apply them in R. No previous experience or knowledge of survival analysis is necessary.
Venue – PS statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map
Availability – 20 places
Duration – 5 days
Contact hours – Approx. 28 hours
ECT’s – Equal to 3 ECT’s
Language – English
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, welcome dinner Monday evening, farewell dinner Friday evening, refreshments and accommodation. Self-catering facilities are available in the accommodation. Accommodation is approximately a 6-minute walk from the PR statistics head office. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 20th January (after 5pm) and departure Friday 25th January (accommodation must be vacated by 9am). An additional nights accommodation can be purchased, departure 9am Friday morning email for details.
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Cancellation policy: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact firstname.lastname@example.org Failure to attend will result in the full cost of the course being charged. In the unfortunate event that PS statistics must cancel this course due to unforeseen circumstances a full refund for the course will be credited. However PS statistics cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.
Dr Will Hoppitt
Introductory lectures on the concepts and refreshers on R usage. Intermediate-level lectures interspersed with hands-on mini practicals and longer projects. Round-table discussions about the analysis requirements of attendees (option for them to bring their own data). Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data.
Assumed quantitative knowledge
A good understanding of statistical concepts, statistical significance and hypothesis testing.
Assumed computer background
R experience is desirable but not essential. Attendees ideally should be able to import/export data, understand basic R syntax and write simple functions and loops.
Equipment and software requirements
A laptop/personal computer with a working version of R or RStudio. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links.
It is essential that you come with all necessary software and packages already installed (you will be sent a list of packages prior to the course) as internet access may not always be available.
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Meet at 43 Cook Street, Glasgow G5 8JN at approx. 17:00 onwards
Monday 21st – Classes from 09:30 to 17:30
Module 1: Statistical modelling of rates and times
Module 2: Parametric survival models and the Cox model
Tuesday 22nd – Classes from 09:30 to 17:30
Module 3: Fitting Cox models
Module 4: Interpreting Cox Models
Wednesday 23rd – Classes from 09:30 to 17:30
Module 5: Evaluating the proportional hazard assumption
Module 6: Stratified Cox models
Thursday 24th – Classes from 09:30 to 17:30
Module 7: Time dependent variables
Module 8: Frailty Models and Multistate models
Friday 25th – Classes from 09:30 to 17:30
Module 9: Competing risks models
Module 10: Open session