This course provides an overview of the fundamentals of quantitative medicine. The principles of biomedical research are discussed and how these together form the building blocks towards evidence-based medicine. There will be thorough discussion on how...

This course introduces the principles of systematic reviews and meta-analysis, with a focus on the potentials and limitations of this study design, including the problematic, massive rise of such analyses in the literature. The identification and...

The field of public health has developed a distinctive way of approaching human health by shifting its focus from the health of individuals to the health of populations. This course revisits the history of this population thinking and how it has helped...

The aim of this course is to provide theoretical and practical training for biostatisticians, epidemiologists, medical researchers and professionals of related disciplines in statistical modeling with particular emphasis on logistic regression. The...

The key aim of this course is to learn about the principal issues surrounding global health and the main outcome of the course will be a better understanding of how epidemiology and public health can more effectively protect the health of disadvantaged...

This course aims to provide a basic introduction to the methods used in classical genetic epidemiology. In combination with the course Analysis of Genome-wide Association...

Formulating a research question, considering the design of a study, collecting data, analyzing data and
reporting of findings are crucial steps in any scientific research. However, other aspects that are equally
important often receive less...

This course aims to bridge the gap between theoretical epidemiological concepts and application in clinical research and medicine. Understanding of basic epidemiological principles is therefore a prerequisite.
Students will learn how abstract concepts...

The goal of many epidemiologic studies is to quantify the causal effect of a treatment (or exposure) on an outcome. In contrast, commonly used statistical methods provide measures of association that may lack a causal interpretation even when the...

The Bayesian approach is an important alternative to the classical (called frequentist) approach to statistics. Indeed, the Bayesian approach has become increasingly important over the last three decades and is invading in all application areas....

This course will provide an introduction to health care decision making. Given uncertainty, trade-offs and values, how should patients, policymakers and clinicians decide among diagnostic and therapeutic choices to make optimal decisions? Medical...

Public health faces several challenges, including widening social inequalities, climate change, rapid urbanization, ageing, and perhaps even new pandemics. What they have in common, is that single (randomised) interventions are insufficiently capable of...

Data science is a multidisciplinary field that brings together domain knowledge with expertise from mathematics, statistics, computer science, engineering, and epidemiology. By combining scientific methods and analytical techniques, it helps transform...

In follow-up studies, different types of outcomes are collected for each subject. These include longitudinally measured responses (e.g., biomarkers) and the time until an event of interest occurs (e.g., disease onset or death). These outcomes are often...

This course will discuss recent developments in epidemiologic methods for clinical research. It will review the various study designs and major issues in the validity of clinical epidemiologic studies. Advances in the design of clinical trials will be...

To realize gender equality in health care, sex and gender dimension needs to be integrated in all aspects of research and clinical practice. This course brings together experts from a multitude of disciplines including clinical, basic science, public...

The course covers recent developments in causal mediation analysis and provides practical tools to implement these techniques. Mediation analysis concerns assessing the mechanisms and pathways by which causal effects operate. The course covers the...

Genome-wide association studies (GWAS) constitute a powerful approach to investigate the genetic basis of complex traits and disorders. The course consists of lectures that provide a conceptual framework for crucial aspects of genetic association,...

Machine learning (and data science in general) is a multi-disciplinary field in which – besides domain-specific expertise – several fundamental scientific disciplines converge, including mathematics, statistics, computer science, engineering and...