Graduate School of health and Medical Sciences

Epidemiology 2: Analysing data from observational studies
Provider: Faculty of Health and Medical Sciences

Activity no.: 3124-24-00-00	There are no available seats
	Enrollment deadline: 10/09/2024

Date and time	21.10.2024, at: 08:00 - 15.12.2024, at: 16:00
Regular seats	12
Course fee	12,600.00 kr.
Lecturers	Carsten Kirkeby
ECTS credits	6.00

Contact person	Søren Nielsen E-mail address: saxmose@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@sund.ku.dk

Aim and content This course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD Students from NorDoc member faculties. All other participants must pay the course fee. Anyone can apply for the course, but if you are not a PhD student at a Danish university, you will be placed on the waiting list until enrollment deadline. This also applies to PhD students from NorDoc member faculties. After the enrollment deadline, available seats will be allocated to applicants on the waiting list. Learning objectives A student who has met the objectives of the course will be able to: 1. Identify an epidemiological problem to be investigated using relevant analytical methods. Specifically, the participant should be able to identify and address potential problems in the data, such as bias and/or confounding and clustering. 2. Use relevant epidemiological and statistical methods for descriptive and analytical epidemiological studies 3. Conduct simple epidemiological analyses independently 4. Collaborate scientifically with epidemiologists and statisticians and other relevant scientists on epidemiological problems going beyond this course 5. Evaluate the validity and reliability of the epidemiological results and assess generalisation to other populations than the study population Content The course focuses on epidemiological analysis of continuous and dichotomous data. Hypothesis establishment and testing, along with assessment of causality and bias are carried out. Methods include linear regression, analysis of variance, chi-square test, logistic regression and logistic analysis, multivariable logistic analysis, interaction and confounding. Emphasis will be given to analyses of the participants own epidemiological data. Participants are strongly encouraged to bring their own data. However, the data must be in a form and complexity suitable for the course, i.e. pre-approval of data is a necessity. Otherwise, data will be provided. During the course, the participant has to analyse the data at hand, starting with specification of testable objectives, description of population, data analysis and results presentation. This should result in a report that can eventually be submitted as a paper to a scientific journal. The participants will likely present a variety of epidemiological studies from human and veterinary medicine. These different studies will be used in a continuous peer-review process throughout the course to strengthen the application of epidemiological methodology. The software R will be used for the data analyses Participants The participants are required to have passed the course “Epidemiology 1: Planning a Study” or a similar course. Furthermore, participants are required to have basic R-skills as taught in that course, i.e. minimum 40 hours of practice using R. These skills may be obtained through self-studies prior to the course. 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: Herd and Population-oriented Research (HERD) All graduate programmes Language English Form The course is taught as eLearning in weeks 43-49, with exam held in week 50. Individual arrangements are made in planning of the exam, which can take place online for participants not from the Copenhagen area. Two days on-campus training supplement the elearning. During the course, the participant has to present parts of a report step-by-step, which will ultimately form the basis for the exam (and a draft manuscript suitable for publication in a peer-reviewed scientific journal). The contents and data analyses are discussed with the other participants during the course. This basically means that the participant is required to hand in several assignments each week and ultimately pass an exam to pass the course Course director Søren Saxmose Nielsen, Professor, Department of Veterinary and Animal Sciences, saxmose@sund.ku.dk Carsten Thure Kirkeby, Senior Researcher, Department of Veterinary and Animal Sciences, ckir@sund.ku.dk Teachers Søren Saxmose Nielsen, Professor, Department of Veterinary and Animal Sciences, saxmose@sund.ku.dk Carsten Thure Kirkeby, Senior Researcher, Department of Veterinary and Animal Sciences, ckir@sund.ku.dk Matt Denwood, Professor, Department of Veteriinary and Animal Sciences Dates 21 October – 15 December 2024 On-campus workshop dates: 5-6 November 2024 eLearning – 10-20 hours per week. Weekly assignments should be expected Course location Distance-based (UCPH’s eLearning environment Absalon) A stable internet connection is required. The two workshop days are at University of Copenhagen, Frederiksberg Campus Registration Please register before 10 September 2024 Expected frequency Once a year 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. 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.

Click the search button to search Courses.

See which courses you can attend and when

Jan	Feb	Mar	Apr
May	Jun	Jul	Aug
Sep	Oct	Nov	Dec

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

Learn which courses are announced on fixed dates