Statistical Practice in Epidemiology using
R
.
Monday 2 June to Friday 6 June 2025
at University of Tartu in
Tartu, Estonia
The course starts early morning Monday, so arrival in Tartu must be
on Sunday 1st.
The course ends on Friday at 14:00.
Similar courses were given every year since 2000 with the exception of
2003, 2008 and 2020-2022.
Audience
The course is intended for epidemiologists and statisticians who wish
to use R
for
statistical modelling and analysis of epidemiological data.
The aim of the course is to give young statisticians (or not so young
epidemiologists) who wish to enter or who has recently entered
biostatistics or epidemiology access to a set of tools in current use
by statisticians in epidemiology.
The course requires basic knowledge of epidemiological concepts and
study types. These will only be briefly reviewed, whereas the more
advanced epidemiological and statistical concepts will be treated in
depth.
Contents
- History of
R
. Language. Objects. Functions.
- Interface to other dataformats. Dataframes.
- Tabulation of data.
- Logistic regression for case-control-studies.
- Poisson regression for follow-up studies.
- Causal inference.
- Parametrization of models.
- Graphics in
R
.
- Graphical reporting of results.
- Time-splitting & SMR.
- Nested and matched case-control studies.
- Case-cohort studies.
- Survival analysis in continuous time.
- Competing risk models and relative survival.
- Multistate models.
All methods will be thoroughly illustrated using R
in practical
exercises.
The Epi package
which is developed for epidemiological analysis in R
will be introduced.
Special attention will be given to the reporting of the results; in
particular the use of graphics.
Faculty:
- Janne Pitkäniemi,
Professor of Cancer Epidemiology,
University of Tampere, Finland
Director, Finnish Cancer Registry, Helsinki, Finland
Department of Public Health, University of Helsinki, Finland
-
Damien Georges,
Senior Research assistant,
Early Detection, Prevention, and Infections Branch,
International Agency for Research on Cancer, Lyon, France.
- Bendix Carstensen,
Senior Statistician,
Steno Diabetes Center Copenhagen &
Department of Biostatistics, University of Copenhagen,
Denmark. Maintainer of the Epi package.
- Krista Fischer,
Professor,
Institute of Mathematics and Statistics and
Institute of Genomics, University of Tartu, Estonia
- Esa
Läärä,
Professor emeritus of Biometry,
Research Unit of Mathematical Sciences, University of Oulu,
Finland.
-
Martyn Plummer,
Professor of Statistics,
University of Warwick, UK.
Member of the
R
core team.
The entire faculty will be present through most of the course, so the
course has an unusually large faculty / student ratio.
Venue
Delta Centre, University of Tartu,
Narva
Mnt 18, 51009 Tartu
Course fee:
- academic participants: 1000 EUR
- non-academic participants: 1200 EUR
Includes course, access to course material, coffee breaks and
catered social events.
Excludes transport, accommodation and meals (onsite cafeteria
available with a range of inexpensive lunch options).
The course is a self-supporting entity, and there are NO grants
or stipends available for travel or participation.
Registration:
Send an e-mail briefly stating your qualifications in epidemiology and
statistics, to
Anastassia Kolde
Subject line of the mail should be in the format "SPE25 name surname".
Applications will be considered in the
order they are received, following the first-come, first-served
principle.
Deadline: 1 April 2025
After the application deadline we will send you information regarding
the registration and accommodation.
Prerequisites
- Make sure you have the latest version of
R
4.4.3
(here, for
example), and install it.
- Install the
R
-package Epi
, from
here
or by starting R
and then typing:
> install.packages("Epi")
at the command prompt in R
. If you have an older version of
Epi
, then update
to version 2.59.
- Install the
R
-packages
data.table
,
popEpi
and
epitools
by starting R
and then typing:
> install.packages("data.table")
> install.packages("popEpi")
> install.packages("epitools")
at the command prompt in R
. This requires that your
computer is connected to the net.
-
Concepts in survival and demography
is a brief account of basic concepts and their
relationships.
Accomodation:
We have reserved a number of rooms at hotels/guesthouses in Tartu at moderate
prices, and within walking distance from the course venue (everything
is basically within walking distance in Tartu).
Transport and getting around in Tartu
Tartu
is situated 185 km south-east of the Estonian captal
Tallinn. Transportation is by air (or sea from Helsinki) to Tallinn
and from there approximately 2.5 hrs. by
bus or
train. The bus calls at Tallinn
airport, the train can be boarded at Ülemiste station, close to the
airport.
There is also
an airport in Tartu,
though thinly serviced.
For more information on transport to and around
Tartu, look here.
Last updated 10 March 2025, BxC