|Teaching method||Contact hours|
|Course coordinator(s)||dr. ir. AM Berendsen|
|Lecturer(s)||prof. dr. HC Boshuizen|
|prof. dr. ir. EJM Feskens|
|dr. FJB van Duijnhoven|
|dr. ir. AM Berendsen|
|Examiner(s)||dr. FJB van Duijnhoven|
Language of instruction:
Assumed knowledge on:
- (MAT-15303 Statistics 1 + MAT-15403 Statistics 2) or MAT-14303 Basic Statistics
- MAT-24306 Advanced Statistics for Nutritionists
- HNH-24806 Introduction to Epidemiology and Public Health
- HNH-31006 Study Design and Interpretation in Epidemiology and Public Health
- HNH-3AA06 Analytical Epidemiology II;
- Thesis Nutrition and Disease;
- Thesis Global Nutrition
THIS COURSE WILL BE TAUGHT FOR THE FIRST TIME IN THE 2019/2020 ACADEMIC YEAR.
IT IS A NEW, EXTENDED VERSION OF HNH-37306 APPLIED DATA ANALYSIS WITH PARTS OF HNH-30806 ANALYTICAL EPIDEMIOLOGY AND HAS SIGNIFICANT OVERLAP WITH THOSE COURSES.
This new course can not be combined in an individual study programme together with the two courses mentioned, when in doubt, contact your study adviser. This course can not be combined in an individual programme with HNH-33403 Advanced Analytical Epidemiology (online) and/or HNH-35903 Integration of evidence II (online).
Interpretation and analysis of results from nutrition & health research in humans requires understanding of the close interrelationship between the main study designs and methods of data analysis. During this course, the students will learn to conduct and interpret data analysis in the framework of various types of observational studies using statistics as their main tool. Aspects concerning data-handling and interpretation of effect measures and of statistical models is an important part of this course.
After successful completion of this course students are expected to be able to analyse data of cross-sectional, longitudinal, case-control and cohort studies, i.e.:
- to choose the appropriate method of data analysis, given the study design and type of variables;
- to execute and interpret descriptive statistics;
- to execute and interpret results of linear regression models, logistic regression models, general and generalized linear models, mixed models, and Cox proportional hazard models;
- to understand how stratification and regression analysis can be used to evaluate confounding and effect measure modification and is able to perform these methods;
- to understand the principles and procedures of energy-adjustment and is able to adjust for energy using different methods.
- E-modules and exercises on the computer;
- (individual and/or group) assignments;
- self study.
Will be announced in the course guide.
Course materials, e.g. literature (papers), e-modules, exercises, assignments, handouts of lectures, and announcements will be made available in Brightspace. Students are urgently recommended to make notes during the computer practicals, because study material is included in the exercises and e-modules.
|Compulsory for:||MNH||Nutrition and Health||MSc||A: Nutritional and Public Health Epidemiology||4WD|