Dr Peter Blair (course organiser), Prof Yoav Ben Shlomo, Prof David Gunnell, Dr Matthew Hickman, Prof Debbie Lawlor, Prof Richard Martin, Dr Chris Metcalfe, Dr Alan Montgomery, Prof Andy Ness, Dr Petros Skapinakis,Dr John Macleod,Dr Stan Zammit,Dr Sara Brookes, Dr Caroline Trotter,Dr Raghu Lingham.
The contributors are epidemiologists and medical statisticians and have wide-ranging interests in clinical epidemiology. They have a breadth of experience in the design, conduct and analysis of epidemiological research.
21 - 25 January 2013
The aim of the course is to provide a grounding in epidemiological study designs and measures of disease risk used in aetiological epidemiology and health services research. Participants will gain practical experience in study design and the appraisal of epidemiological literature.
appreciate the importance of epidemiological research methods in aetiological epidemiology and health services research;
understand relevant summary measures relating exposures to disease risk;
select appropriate epidemiological study designs to answer particular research questions;
understand the strengths and weaknesses of different epidemiological study designs;
be able to assess possible reasons for observed exposure-disease associations;
assess causality using the Bradford Hill criteria.
This course is intended for clinicians, researchers, public health specialists and other health care professionals who have only a basic understanding of epidemiology. Prior knowledge of basic medical statistics so that you understand findings published in peer-reviewed medical journals is important. No prior knowledge of Stata is required. Please bring a calculator.
Topics to be covered include: exposure measurement and measures of disease occurrence (incidence, prevalence); measures of exposure effect (risk, rate
and odds ratios); study designs (cross-sectional studies, case-control studies, cohort studies, ecological studies and randomised controlled trials); bias and confounding; basic regression, interaction; sample size calculations; causal Inference; epidemiology and public health policy.
Teaching will comprise thirty hours of lectures, practical exercises, revision sessions and group discussions.
This course assumes that you understand how to interpret most findings in medical journals but if you want to refresh your basic knowledge of stats then you could buy a book such as Medical Statistics Made Easy by M Harris and G Taylor (Second Edition). Published By Martin Dunitz Taylor & Francis Group 2003. Pb: 1-84184-219-X
For further information please contact firstname.lastname@example.org