Login for PhD students at UCPH      Login for others
Advanced statistical analysis of epidemiological studies
Provider: Faculty of Health and Medical Sciences

Activity no.: 3306-22-00-00There are no available seats 
Enrollment deadline: 23/09/2022
Date and time24.10.2022, at: 10:00 - 05.12.2022, at: 17:00
Regular seats24
Course fee5,040.00 kr.
LecturersPer Kragh Andersen
ECTS credits4.20
Contact personSusanne Kragskov Laupstad    E-mail address: skl@sund.ku.dk
Enrolment Handling/Course OrganiserPhD administration     E-mail address: phdkursus@sund.ku.dk

Aim and content
This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH.

Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list.

The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member universities. All other participants must pay the course fee.


Aim and learning objectives
The course builds on the Ph.D.-course in Epidemiological methods in medical research. The purpose is to give an introduction to more advanced statistical methods frequently applied in epidemiological studies. After completing the course the participants will:

• be able to analyse data from classical cohort studies using Poisson or Cox regression and data from case-control studies using ordinary or conditional logistic regression

• know about the advantages of using cohort data sampled as a nested case-control study or a case-cohort study

• know about methods for analysing clustered data

• know about methods to account for competing risks and recurrent events in follow-up studies

• know about the basic concepts for causal inference


Content
Repetition of logistic regression, Poisson regression, and Cox regression. Time-dependent exposure variables. Conditional logistic regression for matched case-control studies. Alternative designs of cohort studies: Nested case-control- and case-cohort studies. Analysis of correlated data. Longitudinal studies. Competing risks. Recurrent events. Introduction to causal inference.

Textbook:
D. Clayton & M. Hills (1993). Statistical Models in Epidemiology. Oxford Univ. Press and supplementary material.

Participants
Ph.D.-students with a background corresponding to the course “Epidemiological methods in medical research” held every Spring. Max. 24 participants.


Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:
ALL GRADUATE PROGRAMMES

Language
Danish or English.

Form
6 full days of lectures and computer exercises using primarily SAS or R. Participants must bring a laptop with the desired software installed.

Course director
Professor Per Kragh Andersen

Teachers
Members of the staff of Department of Biostatistics and external teachers.

Course secretary
Susanne Kragskov Laupstad, Department of Biostatistics, e-mail: skl@sund.ku.dk

Dates
Mondays 24, 31 October, 7, 21, 28, November, 5 December 2022, all days 10-17

Course location
CSS

Registration
Please register before 23 September 2022


Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrolment.


Formel requirements
You must have taken the course in epidemiology.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor..

Search
Click the search button to search Courses.


Course calendar
See which courses you can attend and when
JanFebMarApr
MayJunJulAug
SepOctNovDec



New courses
Courses are published regularly. High demand courses are announced in spring and autumn.


Learn which courses are announced on fixed dates