Principles of Epidemiologic Data-analysis [EWP25]
Monday to Friday (5 mornings)
Prof. Kenneth Rothman, MD, PhD
Erasmus MC, Rotterdam NL
A course on epidemiologic study design.
Detailed information about this course:
The course will present the basic precepts and the principles underlying the primary methods of epidemiologic data analysis.
The aim of the course is for the participant to arrive at a coherent conceptualization of the core principles of epidemiologic data analysis. This is not a statistics course; although examples of analytic calculations are given and there are lab exercises assigned for homework, there is no emphasis on proficiency in the execution and calculation of results nor how to build mathematical models.
The course begins with a discussion of the principles of epidemiologic data analysis, and then progresses to a discussion of precision and validity, placing a strong emphasis on a quantitative approach to analysis, using estimation, rather than a qualitative approach based on statistical significance testing. After covering the analysis of crude data, the focus shifts to the control of confounding using stratified analysis and multivariate models. Other topics that are covered include the analysis of matched data, the evaluation of interaction, the use of multivariate summary confounder scores (including propensity scores), marginal structural models, imputation of missing data, sensitivity analysis, and the estimation of trends in effect.
The class presentations will be supplemented with discussion of selected published papers and computer assignments using the Episheet spreadsheet to illustrate key analytic concepts.
The course consists of lectures, case studies involving reading and classroom discussion, and assignments using a spreadsheet for epidemiologic data analysis, which is supplied.
- Students will become conversant with the principles of estimation of epidemiologic measures from basic epidemiologic data.
- Students will be able to explain and demonstrate the advantages of stratified analysis as a primary approach to epidemiologic data analysis, and to use a spreadsheet program to conduct basic epidemiologic analysis of stratified data, and to interpret the results.
- Students will be able to describe a strategy for using regression models in epidemiologic data analysis, either using an outcome model or a model that serves as a confounder summary score.
Anyone with an interest in the principles of epidemiologic data analysis may apply. It is recommended that applicants have completed a course in epidemiologic study design.
Attendance, Written exam
Reduction on fees
50% reduction on our fees for participating institutes of NIHES
This 50% reduction is offered to participants appointed at the departments or sections participating in NIHES.
University Medical Center Rotterdam/Erasmus University Rotterdam:
- Department of Epidemiology
- Department of Public Health
- Department of Psychiatry, Section of Medical Psychology and Psychotherapy
- Department of Child and Adolescent Psychiatry/Psychology
- Department of Health Policy and Management
- Department of Medical Informatics
- Department of General Practice
50% reduction on our fees for NIHES affiliated partners
This 50% reduction is offered to participants appointed at the following NIHES affiliated partners:
University Medical Center Rotterdam/Erasmus University Rotterdam, departments of:
- Plastic and Reconstructive Surgery
- Rehabilitation Medicine
Institute of Medical Education Research Rotterdam (iMERR)
Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital
- Department of Cancer Epidemiology
25% reduction on our fees for partner institutes of NIHES
For participants appointed at the following departments, institutes:
- Departments of Erasmus MC (except the departments mentioned above)
- Addiction Research Institute (IVO)
- Integraal Kankercentrum Zuid (IKZ)
- Pallas Health Research and Consultancy
- Municipal Health Service Amsterdam (GGD Amsterdam)
- Municipal Health Service Rotterdam (GGD Rotterdam)
25% reduction for all (international) PhD students
Please state your tutor’s name and email address on the application form (remarks field).