Biostatistical Methods II: Classical Regression Models [EP03]
Full weekdays, except Wednesdays during the first two weeks. The third week is a study week.
Prof. Dimitris Rizopoulos, PhD, Dr. Sten Willemsen
Erasmus MC, Rotterdam NL
Biostatistical Methods I: Basis Principles (CC02) and the Introduction to R course of NIHES. If you have been registered for the EP03 course, you will be automatically enrolled in the Introduction to R course, a short online course. NIHES checks whether you meet the prerequisite for EP03.
Detailed information about this course:
The aim of this course is to introduce several important statistical regression models for non-normal and censored outcomes that are widely applied in clinical and epidemiological research. The course starts with a brief presentation of the basic principles behind likelihood theory, followed by a detailed discussion of logistic regression for dichotomous data, Poisson regression for count data, and closes with an extended presentation of regression models for time-to-event data, including the Cox proportional hazards model and the accelerated failure time model.The course will be explanatory rather than mathematically rigorous, with emphasis given on application such that participants will obtain a clear view on the different modeling approaches, and how they should be used in practice.
To this end, the course includes several computer sessions during which participants will be asked to implement in practice the methods discussed in the theory sessions. Oral exam will be on two days: December 7 and 8, 2017, and the assignment will be due three days prior to the oral exam.
After this course participants will be able to identify which type of regression models should be utilized depending on the nature of the data at hand and the actual research questions to be answered, and which model-building strategies should be followed in each setting. Furthermore, participants should be able to construct and fit an appropriate regression model, correctly interpret the obtained results, and extract additional useful information (e.g., plots) that can help communicate the results of the analysis.
For researchers wanting to learn the basics of regression analysis.
Oral exam, Assignment(s)
Reduction on fees
PLEASE NOTE THIS DOES NOT APPLY TO THE RESEARCH MASTERS (120 ECTS)
50% reduction on our fees for participating institutes of NIHES
This 50% reduction is offered to participants formally 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 Medical Informatics
- Department of General Practice
- Erasmus School of Health Policy & Management
- Generation R
50% reduction on our fees for NIHES affiliated partners
This 50% reduction is offered to participants formally appointed at the following NIHES affiliated partners:
University Medical Center Rotterdam/Erasmus University Rotterdam, departments of:
- General Paediatrics
- 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 formally 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)
- Admiraal De Ruyter Ziekenhuis
25% reduction for all (international) PhD students
Please state your tutor’s name and email address on the application form (remarks field).
25% reduction on our course fees (maximum 3 EC points per academic year) for all NIHES alumni
Please state that you are a NIHES alumnus/alumna and the academic year you graduated (remarks field).