A 3-day course on Statistical Methods for Risk Prediction and Prognostic
Models
DATE: 19th - 21st November 2018
LOCATION: Keele University, UK
OVERVIEW: Patients and their care providers often want to know the risk of
developing an (adverse) health outcome over time. Estimates of future risk
('prognosis') allow patients and their families to put a clinical diagnosis
into context, and help care providers to make clinical decisions and devise
treatment strategies. For this purpose there is a growing interest in risk
prediction and prognostic models. This 3-day course provides a thorough
foundation of the statistical methods most commonly needed to develop and
validate prognostic and prediction models in clinical research. A mixture
of lectures and computer practical sessions in Stata and R are used to
ensure participants appreciate the underlying statistical concepts and can
apply the methods learned to real datasets for either binary or
time-to-event outcomes.
The course is delivered over 3 days, and focuses on model development (day
1), internal validation (day 2), and external validation and novel topics
(day 3). Our focus is on multivariable models for individualised prediction
of future outcomes (prognosis), although many of the concepts described
also apply to models for predicting existing disease (diagnosis).
TARGET AUDIENCE: The course is aimed at individuals that want to learn how
to develop and validate risk prediction and prognostic models, specifically
for binary or time-to-event clinical outcomes. We recommend participants
have a background in statistics. An understanding of key statistical
principles and measures (such as effect estimates, confidence intervals and
p-values) and the ability to apply and interpret regression models is
essential. We also recommend that participants are familiar with Stata,
although the practicals will not require individuals to write their own
code. Participants will need to bring a laptop with R or Stata version 12
or above installed. It may be possible to borrow a laptop on the day, but
this must be agreed in advance.
COURSE FACULTY: Dr Kym Snell, Prof Richard Riley, Dr Joie Ensor, Ms Lucy
Teece (Keele University)
Prof Gary Collins (University of Oxford)
Dr Laura Bonnett (University of Liverpool)
For further information and to register, please follow the link:
https://www.keele.ac.uk/predictionmodelling/
For queries, please contact Kym Snell ([log in to unmask]) or Sue Weir (
[log in to unmask]).
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