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Programmes & specializations videos

Postgraduate Programme | 1 Year | FULL-TIME

For whom?

Consider one additional year of research training after your Master’s, if you’d like to acquire more research experience or increase your chances of qualifying for a PhD research project.

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  • Public Health Epidemiology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Erasmus Summer Programme (ESP)

    For more information about the Erasmus Summer Programme (ESP), please go to:

    www.erasmussummerprogramme.nl

    Master

    Master of Science in Health Sciences | 1 Year | FULL-TIME | 70 EC points

    For whom?

    This MSc programme focuses on training students who are already educated in research methodology, but wish to take a step further in developing a successful career in health science research. This programme is also interesting if you want to enhance your chances of pursuing a PhD.

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  • Public Health Epidemiology
  • Biostatistics
  • Medical Psychology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Research Master in Clinical Research | 2 Years | FULL-TIME | 120 EC points

    For whom?

    This Research Master programme provides a unique opportunity for ambitious students with a Bachelor degree in Medicine or Biomedical Sciences.There is a great need for clinicians who can combine patient care and research. This Research Master programme helps medical students to become clinical investigators and pursue an academic career simultaneously.

    If you are a medical student of Erasmus MC, we have accustomed the Research Master programme to your Master in Medicine.

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    Research Master in Health Sciences | 2 Years | FULL-TIME | 120 EC points

    For whom?

    Just graduated with a Bachelor Degree in clinical, public health or biomedical sciences and want to start making substantial contributions to future developments in medicine as a researcher? Then this Research Master is for you! With a wide range of specialisations and guidance from some of the greatest minds in these fields, you will be well on your way to a very successful research career.


    If you are a medical student of Erasmus MC, we have accustomed the Research Master programme to your Bachelor and Master in Medicine.

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  • Public Health Epidemiology
  • Health Economic Analysis
  • Biostatistics
  • Medical Psychology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Doctorate

    Postgraduate Programme | 1 Year | FULL-TIME

    For whom?

    Consider one additional year of research training after your Master’s, if you’d like to acquire more research experience or increase your chances of qualifying for a PhD research project.

    Read More
  • Public Health Epidemiology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Executive Education

    Executive Master of Science in Health Sciences | 2(+)years | Part-time | 70 EC points

    For whom?

    This Executive Master programme focuses on training individuals who have already  authored scientific publications, but wish to take a step further in developing a successful career in health science research. The programme is ideal for working professionals since you can fully customize it to fit your busy schedule.

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  • Public Health Epidemiology
  • Biostatistics
  • Medical Psychology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Health Decision Sciences
  • Courses

    30 Oct 2019 - 15 Nov 2019
    Clinical Epidemiology [CE02]

    About this course

    Research questions in clinical epidemiology originate from clinical practice. Caring for patients commonly triggers the research-minded clinician to question his/her knowledge and decisions. Questions may revolve around risk factors, prevention, diagnosis, prognosis and/or interventions. Results from clinical epidemiological research are used in patient management decisions. Concepts from decision sciences are used to translate clinical research results to application in day-to-day clinical practice.

    In this course, the principles and practice of clinical epidemiology and the application of the results to clinical decision making will be considered, using examples from the literature and from ongoing studies.

    We will be using blended learning: a combination of web-based materials, interactive lectures, workshops and practicums.

    The course is divided into 3 parts:

    1. Diagnosis
    2. Prognosis
    3. Interventions

    Assignments for each part need to be completed prior to the next part.

    Read More

    28 Oct 2019 - 1 Nov 2019
    Public Health Research: Analysis of Determinants [HS02b]

    About this course

    Public Health Research: from Epidemiology to Health Promotion

    Module: Analysis of Determinants

    This module elaborates on research of the analysis of determinants of and inequalities in population health and risk factors of disease. Students will be introduced in:

    • current insights in the main determinants of population health and risk factors of disease;
    • determinants of inequalities in population health;
    • research methods for the analysis of these determinants and
    • challenges for future research in these issues.

    Read More

    27 Jan 2020 - 31 Jan 2020
    Advanced Topics in Decision-making in Medicine [EWP02]

    About this course

    This course deals with intermediate- to advanced level topics in the field of medical decision making. Topics that will be addressed include building decision models, evaluation of diagnostic tests, utility assessment, multi-attribute utility theory, Markov cohort models, microsimulation state-transition models, calibration and validation of models, probabilistic sensitivity analysis, value of information analysis, and behavioral decision making. The course will focus on the practical application of techniques and will include published examples and a computer practicum. Students will learn to apply state-of-the-art modeling methods (students may choose to use  either Treeage or R (or both)) to evaluate the comparative effectiveness and cost-effectiveness of health interventions. While the primary emphasis is on application, essential underlying theoretical concepts will also be discussed. During the course you will have the opportunity to work on a decision problem which you select yourself. Many students use the course as a way to start writing a paper on a decision model in the field of their interest.

    Please note: this is a challenging course. 

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    26 Aug 2019 - 06 Sept 2019
    Study Design [CC01]

    About this course

    In this course, the principles and practice of follow-up and case-control studies will be taught. The theory underlying the different design options will be discussed in depth. The course focuses on the classical approach but also addresses modern concepts. The practice of conducting follow-up and case-control studies with emphasis on issues of validity will be discussed. Lectures will be complemented by exercises using current examples of epidemiological studies.

    Participants will be asked to work out a study design and prepare a formal presentation on the last course day.

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    25 Nov 2019 - 6 Dec 2019
    Biostatistical Methods II: Classical Regression Models [EP03]

    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.

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    23 Apr 2019 - 26 Apr 2019
    From Problem to Solution in Public Health [HS18]

    About this course

    The current challenges in public health require a strong link between science, policy and practice. This link is bi-directional. Professionals in practice can use their vast experience to guide better and more targeted research. Policy makers can identify which solutions may work or not and researchers can provide better evidence for public health programmes.


    In two Master Classes experienced researchers and policy makers will work together with participants on major public health problems. The public health problems selected are addiction & substance use, and injuries. Through intensive interaction participants will learn (1) how to make a comprehensive analysis of the problem, (2) how this analysis will guide the required evidence-base for tackling the problems, and (3) how to plan and evaluate appropriate preventive interventions.


    The Master Classes are restricted to 25 participants and will require an intense, active participation.

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    21 May 2019 - 07 Jun 2019
    Introduction to Medical Writing [SC02]

    About this course

    During the second semester, full time Master of Science (70 ECTS) students will attend four workshops of three hours and one workshop of six hours on how to write correct and readable scientific articles in English. Each student will be able to bring their own work which will be commented on and corrected by participants and the teacher.

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    19 Aug 2019 - 23 Aug 2019
    Health Economics [ESP25]

    About this course

    Faculty: Ken Redekop, PhD


    Economic thinking is becoming increasingly important in health care.This course begins with a two day introduction of main concepts of health economics. The remaining three days are used to provide students with more in depth knowledge. The student will learn to analyze the cost-effectiveness of health care interventions (e.g., medicine, diagnostic test, health care programme).

    Both methodology and practical examples will be covered. Exercises are used to illustrate the various steps in economic thinking.

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    19 Aug 2019 - 23 Aug 2019
    Primary and Secondary Prevention Research [ESP45]

    About this course

    Faculty: Prof. Oscar Franco, MD PhD and Nora Pashayan, MD PhD


    This course will introduce and illustrate methods and practices of research in the planning, development and evaluation of interventions to prevent ill health. Primary and secondary prevention may work together, depending on the determinants of disease and technology available. Life style factors, like for example cigarette smoking, dietary habits and physical activity, are important determinants of health and disease. Therefore, promoting healthy life styles is important in public health interventions.

    Screening for diseases that are related to these determinants can possibly improve prognosis, gain life-years and quality of life. However, early detection also means a longer period of life during which a person is aware of having the disease, and false-positive test results will induce unnecessary diagnostic interventions. Crucial in prevention research is the population perspective, with consequences for designing a study, evaluating an intervention, communicating to the people and setting priorities. Special emphasis will be given to cancer research, cardiovascular interventions, but also to preventing language delays in children or promoting alcohol consumption. The course will consist of lectures, exercises and presentations of illustrative examples of primary and secondary prevention research.


    Teaching format: Lectures, exercises, discussions.

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    19 Aug 2019 - 23 Aug 2019
    Social Epidemiology [ESP61]

    About this course

    Faculty: Prof. Frank van Lenthe, PhD


    This course aims to introduce and illustrate modern research methods in social epidemiology, i.e. the study of the social determinants and social outcomes of health. The three main areas to be covered are: the measurement of health inequalities, the explanation of health inequalities, and the evaluation of interventions and policies to reduce health inequalities. Application of the research methods will be illustrated with historical landmark studies as well as recent examples from the international literature.


    The programme consists of lectures, hands-on exercises, and group discussions. The focus will be on socioeconomic inequalities in health, but the role of other social factors (such as ethnicity and marital status) will also be discussed.

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    19 Aug 2019 - 23 Aug 2019
    Practice of Epidemiologic Analysis [ESP65]

    About this course

    Faculty: Kamran Ikram, MD PhD


    This is a course in which the theoretical background and practical application of basic epidemiologic analytic tools is discussed. Special attention will be paid on issues such as normalization, standardization, and categorization, combining multiple variables, combining multiple sources etc. The goal is to provide students with the understanding and tools to perform epidemiologic data analysis.

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    19 Aug 2019 - 23 Aug 2019
    Causal Mediation Analysis [ESP69]

    About this course

    Faculty: Linda Valeri, PhD


    The course will cover some of the recent developments in causal mediation analysis and provide practical tools to implement these techniques. Mediation analysis concerns assessing the mechanisms and pathways by which causal effects operate. The course will cover the relationship between traditional methods for mediation in epidemiology and the social sciences and new methods in causal inference. For dichotomous, continuous, and time-to-event outcomes, discussion will be given as to when the standard approaches to mediation analysis are valid. Using ideas from causal inference and natural direct and indirect effects, alternative mediation analysis techniques will be described when the standard approaches will not work. The no-confounding assumptions needed for these techniques will be described.


    SAS, SPSS and Stata macros to implement these techniques will be covered and distributed to course participants. The use and implementation of sensitivity analysis techniques to assess the how sensitive conclusions are to violations of assumptions will be covered. Discussion will be given to how such mediation analysis approaches can be extended to settings in which data come from a case-control study design. The methods will be illustrated by various applications.


    The course will employ a combination of lecture, discussion, and software demonstration. Powerpoint slides will be used to present material in lecture form. Extensive printed notes will be available for students. A wide variety of examples from epidemiology and the social sciences will be used to illustrate the techniques and approaches. Ample time will be given for discussion and questions. A variety of software packages will be discussed. Students will have worked exercises that they can complete on their own.

    Read More

    19 Aug 2019 - 23 Aug 2019
    Joint Models for Longitudinal and Survival Data [ESP72]

    About this course

    Faculty: Prof. Dimitris Rizopoulos, PhD


    Longitudinal and time-to-event outcomes are the main types of outcomes encountered in medical studies. Primary examples of the former are biomarkers or other patient parameters that are measured during follow-up, whereas for the latter examples include the time to relapse of the disease, time to re-operation or time to death. This course introduces a new type of statistical models that can be used to investigate the association structure between longitudinal and survival outcomes.


    In terms of software, we will use R and illustrate how these models can be fitted using package JM and JMbayes.

    Participants will be expected to bring their own laptop computers to the session, and to have recent versions of R

    (http://www.r-project.org/) and of R packages JM

    (http://cran.r-project.org/package=JM) and JMbayes

    (http://cran.r-project.org/package=JMbayes) already installed on these computers. All necessary computer code will be provided beforehand.

    Read More

    19 Aug 2019 - 23 Aug 2019
    Genome-wide association studies [ESP74]

    About this course

    Faculty: Fernando Rivadeneira, MD PhD


    Genome-wide association studies (GWAS) constitute a powerful approach to investigate the genetic basis of multifactorial disorders. In the last decade, GWAS have yielded spectacular successes in the discovery of genes involved in complex traits and disorders (e.g. body height, BMI, cardiovascular disease, cancer and neurological disorders). This was made possible by the advent of high-throughput genotyping technology and the knowledge on genome structure and organization derived from the HapMap and 1000 Genomes Projects. Applying the GWAS approach has facilitated researchers to incorporate these analyses into large genetic, clinical and epidemiological studies.


    This course aims to introduce epidemiologists, molecular biologists and clinicians into the basic principles of GWAS, addressing aspects of study design, data collection and analysis, extending to the interpretation and follow-up of results. The course consists of lectures providing a conceptual framework on crucial aspects of quality control, imputation of missing genotypes, statistical tools, methods to detect and correct for stratification, meta-analysis and genomic annotation of GWAS signals; accompanied by instructive hands-on computer exercises on the principles of analysis of quantitative traits and disease outcomes using software packages that are available in the public domain.


    The course format will allow interactive break-out discussion sessions on theoretical and practical aspects of running GWAS, together with expert-advice procurement on diverse components of collaborative research within networks and consortia.

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    19 Aug 2019 - 23 Aug 2019
    Human Epigenomics [ESP75]

    About this course

    Faculty: Jordana Bell, PhD


    This course is formerly known as Epigenetics.

    This course aims to give an introduction to epigenetics and epigenomic studies of human disease. The course offers an overview of epigenetic mechanisms and their importance during development and over the life course. Different sources of epigenomic variation will be discussed, as well as approaches to characterize epigenomic variability with the use of modern molecular and bioinformatics methods. The course will then focus on epigenomic studies of human disease, to enable participants to interpret the findings in modern epigenetic research and put these into a functional perspective.

    A laptop is required for computer exercises during the course.

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    19 Aug 2019 - 23 Aug 2019
    Value Based Healthcare, from theory to implementation [ESP76]

    About this course

    Faculty Lead: Prof. Jan Hazelzet, MD PhD

    Overall aim: To provide participants with an overview of all aspects of value-based-health care (VBHC) as theorised by Prof Michael Porter, Harvard Business School. Where value is defined as the outcomes achieved for patients relative to costs. This means measuring provider and patient reported outcomes and costs in a standardized way. But there is more than this. Patient engagement, more specific shared decision making and co-creation, team collaboration and continuous improvement of the care path used are as important. This will be illustrated with clinical examples of multiple organizations. The program consists of 15 lectures and will deal with all the aspects of value based healthcare.

    Halfway the week, on Wednesday August 21, before the start of the course, a network lunch will be organised for all VBHC course participants. Details will be provided to course participants in August.

    CME accreditation for this course is pending.

    Read More

    19 Aug 2019 - 23 Aug 2019
    Gender and Health [ESP78]

    About this course

    Faculty: Dr. Maryam Kavousi MD PhD, Dr. Jeanine Roeters van Lennep MD PhD

    Invited speakers


    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 health and policy and provides participants with resources that will assist them in developing and strengthening gender-equal clinical care and research programs. The course will focus on the critical health issues for women and men through the life cycle, challenges of integrating sex and gender from the health research, practice, and policy perspectives, as well as strategies to address these challenges.


    This course is formerly known as Women’s Health (NIHES EP19).


    Teaching methods: Interactive lectures

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    19 Aug 2019 - 23 Aug 2019
    Gender in Research: Workshops [ESP79]

    About this course

    Faculty: Maryam Kavousi, MD PhD, Coordinator: Miranda van Duijn PhD

    Invited speakers


    During this workshop, we will explain how sex and gender can be included in the various phases of the research process. The workshop will focus on choices in design, methods and analysis. In addition, attention is paid to research team composition, publications and gender-sensitive implementation.


    Our main purpose is to provide participants with insight into methods for incorporating sex and gender in research. Participants will also be divided into small groups to work on several projects. As such, this workshop will serve to form new communities of young, talented researchers who can join forces on addressing different gender-sensitive topics in future.


    Teaching methods:
 Interactive lectures, exercises, practicals

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    19 Aug 2019 - 22 Aug 2019
    Erasmus Summer Lectures [ESP64]

    About this course

    In these lectures, timely topics in study design of epidemiologic and clinical studies will be addressed. Four renowned researchers will address advanced study design issues in a seminar format.


    Moderator Prof. Arfan Ikram, MD PhD


    Read more about the topics and speakers on the Erasmus Summer Lectures page, find this page in the drop-down menu of Programme.

    The lectures are open without registration or fee for participants of the Erasmus Summer Programme, the NIHES programmes, employees of the Erasmus University Medical Center and public at large.

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    18 Nov 2019 - 22 Nov 2019
    Principles in Causal Inference [EP01]

    About this course

    Epidemiologic research often entails asking and trying to answer questions toward understanding the causes and consequences of health outcomes. Answers to such causal questions require us to combine data (e.g., from observational studies) with assumptions to estimate causal effects. This course will teach students to think critically and rigorously about the implications of study design and analysis toward addressing such causal questions. Students will learn formal causal inference "languages" – including the concept of a target trial, causal diagrams, and counterfactual theory – to articulate research questions, inform an analytic approach, and identify threats to validity such as confounding.

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    18 Nov 2019 - 22 Nov 2019
    SNPs and Human Diseases [GE08]

    About this course

    The analysis of DNAvariations, including Single Nucleotide Polymorphisms (SNPs), is a standardresearch approach to understand causes of disease, in particular the so-called"complex" diseases such as diabetes, osteoporosis, cancer, Alzheimerdisease, etc. The field is changing fast with large scale projects (Humangenome, dbSNP, HapMap, 1000genomes, ENCODE) and novel technology beingcontinuously introduced, including Next Generation Sequencing.

    The course will deal with five main topics, which are in logical order:

    • General Introduction and Study design,
    • Bio informatic tools for SNP finding and analysis,
    • Genotyping techniques and DNA management,
    • Data analysis, and
    • Examples of research in which SNPs are used.
    Every day will cover one topic. The programme for every day will consist of four to six presentations, including international speakers, and there are learning-by-doing sessions. The possibility exists for participants to discuss their own data and work. This course is organized by the Molecular Medicine postgraduate school (MolMed) in collaboration with NIHES.For more information and application check the MolMed website.

    Read More

    18 Nov 2019 - 22 Nov 2019
    International Comparison of Health Care Systems [HS03a]

    About this course

    Insight into the structure, process and outcome of health care systems is vital to be able to implement health care reforms that are effective in improving the health system performance. International comparisons of health care systems and the underlying political, organizational and financial arrangements are a multidisciplinary research field with a mixture of quantitative and qualitative methods. This course will present the various methodological approaches and will build on recent national and international experiences with comparative research.


    The course starts with a clear conceptualization and definition of a health care system, definitions of key system components such as the service delivery system (through professionals and institutions), financing, role of the government and role of patients. Health system performance will be discussed in terms of effectiveness, equity and efficiency. Analytical perspectives taken will come from public health as well as from political sciences and economics. The course will also deal with the recent work performed by international organisations such as the WHO and OECD with respect to health system performance measurement and management.

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    16 Oct 2019 - 4 Nov 2019
    Genetic-epidemiologic Research Methods [GE02]

    About this course

    The aim of this course is to introduce participants to the basic principles of genetic epidemiological research.The first part of the course is dedicated to binary traits, covering the basics of probability theory, hypothesis testing, risk calculation in families, and principles of complex segregation analysis. The second part of the course focuses on the genetics of quantitative traits, covering the concept and estimation of heritability and basic quantitative trait linkage analysis using modern genetic analysis software such as SOLAR and MERLIN. In the third part of the course design of genetic epidemiological studies will be discussed. This will be illustrated by practical examples and an assignment to develop a study.During the third week of the course, students will work in groups on this assignment, and will prepare a presentation.

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    16 Sept 2019 - 11 Oct 2019
    Biostatistical Methods I: Basic Principles [CC02]

    About this course

    The analysis of collected data is an inevitable part of almost any medical research project. Consequently, knowledge of and insight in the basic principles of data-analysis are essential for medical researchers. The course CC02 - Biostatistical Methods I: basic principles is designed to teach classical and basic statistical techniques for the analysis of medical research data. The course comprises lectures as well as computer practicals, in which students will apply the widely used statistical software packages SPSS and/or R to work through exercises.

    CC02 consists of two parts. In part A, which lasts one week, basic applications of biostatistics will be introduced, including descriptive statistics, general principles of statistical hypothesis testing, statistical inferences on means and proportions, and interval estimates for association measures. In part B, which last two weeks, more advanced methods will be discussed, including linear correlation and regression, multiple linear regression, analysis of covariance, regression diagnostics, stratified analysis and time-to-event analysis. The logistic regression model and the Cox proportional hazard regression model will be introduced briefly.

    During the lectures, time will be spent on practical examples and exercises. Throughout the course, examples of SPSS- and R-programmes and -output will be demonstrated in relation to the topics that will be discussed.

    Biostatistical Methods I: Basic Principles, part A (CC02A) is equivalent to Introduction to Data-analysis (ESP03) and Biostatistics for Clinicians (EWP22).

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    14 Oct 2019 - 22 Oct 2019
    Clinical Translation of Epidemiology [CE01]

    About this course

    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 from epidemiological theory can be translated to clinically observable phenomena. Tools and skills taught in this course will be readily applicable in clinical research on etiology, efficacy, diagnosis and prognosis. Successful completion of this course will enable students to continue with more formal training in theoretical causal inference as well as advanced courses in clinical effectiveness and clinical epidemiology.

    The course will consist of interactive lectures, working groups, group presentations and an individual assignment. Through in-class exercises the student will be provided with the opportunity to utilize the knowledge covered in the lectures on a study from the recent literature.

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    14 Oct 2019 - 15 Oct 2019
    Linux for Scientists [GE14]

    About this course

    This course aims to teach users of a Linux/UNIX system how to work with the command line interface. After an introduction to some history and basic concepts the basic commands for file and directory manipulation will be discussed. Subsequently, the students will learn how to manage processes as well as input and output redirection, followed by more advanced text processing utilities like 'sed' and 'gawk'.

    The second half of the course shows how to write Bash shell scripts to automate tasks. This knowledge is then used when discussing the Sun Grid Engine job queue system in use on the epib-genstat servers.

    The course will focus on providing hands-on experience, so those who have been using a Linux system for a longer time will be able to skip the parts they already feel comfortable with and move on to more advanced concepts like regular expressions, version control and advanced use of a text editor. 

    Read More

    14 Oct 2019 - 18 Oct 2019
    Public Health Research: Analysis of Population Health [HS02a]

    About this course

    Public Health Research: From Epidemiology to Health Promotion

    Module: Analysis of Population Health

    This module aims to teach methods to assess the health of populations at national and local levels. Students are taught to calculate, apply and interpret population-based measures of mortality, quality of life and disease occurrence. In addition, students learn methods to assess time trends in population health (e.g. APC methods) and to analyse inequalities in health between social groups.


    Note: HS02a, HS02b and HS02c will be tested after the HS02c course!

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    14 Oct 2019 - 8 Nov 2019
    Psychology in Medicine [MP01]

    About this course

    Medical psychologists study the way somatically ill people think, act and feel. The aim of this course is to teach students about psychological determinants of illness and illness behavior, the psychological consequences of somatic illness and psychological care for somatic patients. First, you’ll learn about ‘normal’ reactions to disease. We’ll then focus on abnormal and pathological reactions to somatic illness and on problems that patients might have in adjusting to their disease.


    We will discuss models that explain why some people find it difficult to adjust to their disease, such as the stress coping model and the stress vulnerability model. Other models that will be discussed in this course include the Health Belief Model, the Theory of Planned Behavior and the Stages of Change Model. These models are widely applied by medical psychologists in interventions for somatic patients. Modern neuroscientific models for understanding behaviour and behavioural disorders will be addressed as well.


    In this course, we will focus on various somatic problems, such as diabetes, inflammatory bowel disease, infertility, organ transplantation and chronic pain.


    Finally, basic theories of doctor-patient communication will be discussed, as communication between doctors and patients has become more and more important.


    The learning method in this course is problem-based learning. Furthermore, you will build a new model for understanding a complex and realistic problem in medical psychology.

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    13 May 2019 - 17 May 2019
    Missing Values in Clinical Research [EP16]

    About this course

    Missing data frequently occur in clinical trials as well as observational studies. An important source for missing data are patients who leave the study prematurely, so-called dropouts. Alternatively, intermittent missing data might occur as well.


    When patients are evaluated only once under treatment, then the presence of dropouts makes it hard to comply with the intention-to-treat (ITT) principle. However, when repeated measurements are taken then one can make use of the observed portion of the data to retrieve information on dropouts. Generally, commonly used methods to analyse incomplete data include complete-case (CC) analysis and, in longitudinal studies, an analysis using the last observation carried forward (LOCF). However, these methods rest on strong and unverifiable assumptions about the missing mechanism. Over the last decades, a number of analysis methods have been suggested, providing a valid estimate for, e.g., the treatment effect under less restrictive assumptions.


    The assumptions regarding the dropout mechanism have been classified by Rubin and co-workers as: missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR).


    In the first part of the course we will review various repeated measurements models and indicate under which missing data mechanism they will provide valid estimates of the treatment effect. Finally, since it is impossible to verify that the dropout mechanism is MAR we argue that, to evaluate the robustness of the conclusion, a sensitivity analysis thereby varying the assumption on the dropout mechanism should become a standard procedure when analyzing the results of a clinical trial.


    The second part of the course focuses on multiple imputation (MI), specifically the fully conditional specification (FCS, MICE), which is often considered the gold standard to handle missing data. We will discuss in detail what MI(CE) does, which assumptions need to be met in order for it to perform well, and alternative imputation approaches for settings where MICE is not optimal. The theoretic considerations will be accompanied by demonstrations and short practical sessions in R, and a workflow for doing MI using the R package mice will be proposed.


    Examination for this course consists of two assignments.

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    12 Aug 2019 - 16 Aug 2019
    Regression Analysis [ESP09]

    About this course

    Faculty: Prof. Brian Marx, PhD


    This intermediate level course aims at providing theoretical and practical training for epidemiologists, clinicians and other professionals of related health disciplines in statistical modeling with particular emphasis on straight line linear and multiple regression. Included topics are: review of straight line regression and correlation, ANOVA for straight line regression, appropriateness of straight line model, polynomial regression, multiple regression analysis, partial F-test, dummy/indicator variables, statistical interaction, comparing straight line regressions, analysis of covariance, estimation and interpretation, goodness-of-fit, model selection, collinearity and outlier diagnostics. Additionally, extensions to some generalized linear models, such as logistic (binomial) regression and Poisson regression, will be introduced and interpreted through examples-- thus helping to bridge the material presented in ESP66 (Logistic Regression).


    Written exam on the Friday in the week after ESP (only for NIHES MSc students and for ‘keuzevak students’). Course materials are allowed during the examination. If other students wish to do this exam, they have to pay a fee of €75,- per exam. Credits are 1.9 ECTS when you take the exam, instead of 1.4 ECTS. Please contact NIHES (nihes@erasmusmc.nl) if you wish to register for the exam, at least two weeks before the start of the course.


    This course is equivalent to Regression Analysis for Clinicians (EWP23).

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    12 Aug 2019 - 16 Aug 2019
    Methods of Public Health Research [ESP11]

    About this course

    Faculty: Prof. Lex Burdorf, Ir. PhD


    This course provides an introduction to essential study designs and analytic methods available to public health researchers to describe the influence of important determinants on public health and to evaluate effects of primary preventive intervention on public health. This course focuses on population health rather than individual health and explains why different designs and methods are required, such as ecological studies and multilevel analysis. The course targets three key issues: (1) summary measures of population health, such as life expectancy, (2) measures of association and relative importance of specific causes for population health, such as population attributable fraction, and (3) evaluation of population interventions through community trials and study designs based on natural experiments instead of RCT. Designs and methods will be illustrated in lectures and exercises and application will demonstrate their usefulness in current hot topics, such as health inequalities; causes and consequences of ageing; avoidable diseases such as cancer; and evaluation of complex societal interventions.

    The course will be relevant to those who have a basic knowledge of epidemiology, and who wish to start a career in public health research.

    Teaching methods:
    This course will use lectures, exercises, and group discussion as teaching tools.

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    12 Aug 2019 - 16 Aug 2019
    Pharmaco-epidemiology [ESP21]

    About this course

    Faculty: Prof. Bruno Stricker, PhD


    Pharmaco-epidemiology pertains to the study of the use and of the effects of drugs. It links clinical pharmacology and epidemiology. This course provides, at an intermediate level, the theoretical basis for studying the intended effects as well as the adverse effects of drugs used in humans. The course will mainly focus on drug research after marketing, including post marketing surveillance and drug risk assessment.

    This course is intended for those who already followed introductory courses in study design, data-analysis and principles of research in medicine.

    Teaching methods

    Plenary interactive teaching with real-life examples and exercises

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    12 Aug 2019 - 16 Aug 2019
    Cohort Studies [ESP39]

    About this course

    Faculty: Prof. Javier Nieto


    This course will provide an introduction to the cohort and other longitudinal designs for students with an intermediate level background in epidemiology.It will focus on design and interpretation, emphasizing the principles and complexities of data collection over time and potential biases that may affect cohort data. Topics to be covered include cohort definition, follow-up and definition of outcomes, fixed and time-dependent exposures, quality control, mixed study designs (nested case-control and other studies), and quality assurance and control. The course will also cover the use of the cohort design in clinical/translational research.

    The course will also cover the basic analytic methods appropriate to various types of cohort data, including the application of both non-parametric methods and regression models. The course will be based on lectures as well as small group activities and plenary discussions of exercises. Competencies to be gained in the course include the ability to interpret findings from cohort studies and to apply principles for the design of cohort studies.

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    12 Aug 2019 - 16 Aug 2019
    Case-control Studies [ESP40]

    About this course

    Faculty: Prof. Moyses Szklo, MD PhD


    The course will provide an introduction to the design and analysis of case-control studies. Topics to be covered include case-based case-control, nested case-control and case-cohort designs, selection of cases and controls, the parameter measured by the odds ratio as a function of control selection, matched and unmatched strategies, confounding and common biases, and evaluation of additive and multiplicative interaction in case-control studies. These topics will be discussed in the context of the case-control design as a special way to analyze cohort data. In addition, a discussion of adjustment approaches appropriate to case-control data will be covered, including stratified and regression methods. The course will be based on classroom lectures and small group discussions of exercises.

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    12 Aug 2019 - 16 Aug 2019
    Methods of Health Services Research [ESP42]

    About this course

    Faculty: Prof. Niek Klazinga, MD PhD


    Health Services Research addresses issues such as access and quality of health care delivery, financing and use of health care services, workforce planning, implementation of change and the overall functioning and performance of health care systems.

    This introductory course provides insight in the various research questions, research designs, data-collection methods and analysis methods used in health services research. It puts emphasis on the links between research, policy and practice. The course is organized around lectures and group exercises.

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    12 Aug 2019 - 16 Aug 2019
    Genomics in Molecular Medicine [ESP57]

    About this course

    Faculty: Prof. André Uitterlinden, PhD, Joyce van Meurs, PhD, Fernando Rivadeneira, MD PhD


    Molecular genetics plays an increasingly important role in medical research. The course addresses various molecular principles relevant for genetic epidemiological research. Different approaches to localize disease genes will be discussed. Cloning of disease genes will be discussed from the bench point of view and with the use of modern bioinformatical methods.The course is particularly interesting for clinicians and epidemiologists who wish to be introduced in methods for identifying (complex) disease genes and its practical applications and basic knowledge of molecular biology.

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    12 Aug 2019 - 15 Aug 2019
    Masterclass: Advances in Genomics Research [ESP63]

    About this course

    Moderator Prof. André Uitterlinden, PhD


    In this masterclass, timely topics in genomics research will be addressed. Four renowned researchers will address the latest developments in epigenetics, forensic genomics, personalized medicine, whole genome sequencing, and new genetic variants.

    Read more about the topics and speakers on the masterclass page, find this page in the drop-down menu of Programme.

    The masterclasses are open without registration or fee for participants of the Erasmus Summer Programme, the NIHES programmes, employees of the Erasmus University Medical Center and public at large. For NIHES Master students doing specalisation Genetic Epidemiology this course is compulsory.

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    12 Aug 2019 - 16 Aug 2019
    Introduction to Bayesian Methods in Clinical Research [ESP68]

    About this course

    Faculty: Prof. Emmanuel Lesaffre, PhD


    This course provides an introduction to Bayesian methods with an emphasis on the intuitive ideas and applications. The course treats the basic concepts of the Bayesian approach, such as the prior and posterior distribution and their summary measures (mean, median, credible interval, etc), the posterior predictive distribution. In addition, Bayesian methods for model selection and model evaluation will be treated.


    The Bayesian approach will also be compared, both conceptually as well as practically, with the classical frequentist approach. Markov Chain Monte Carlo techniques are introduced and exemplified in a variety of applications. The Bayesian approach will be illustrated in clinical trials, epidemiological studies, meta-analyses, diagnostic testing, agreement studies, etc. WinBUGS and OpenBUGS will be used as software. But also the use of their interfaces with R, i.e. R2WinBUGS and R2OpenBUGS will be illustrated.


    Course format:

    In the first three days of the course the Bayesian concepts will be explained. Theory and exercises will then be mixed depending on the topic. The final two days will be devoted to particular application areas and have largely a practical flavor. In addition the application of the Bayesian methodology in the medical literature will be highlighted.


    Teaching methods:

    Interactive lectures, exercises, practicals

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    12 Aug 2019 - 16 Aug 2019
    Fundamentals of Medical Decision Making [ESP70]

    About this course

    Faculty: Prof. John Wong, MD


    This course will provide an introduction to health care decision making. Given the uncertainty, trade-offs and values that are involved, how should patients, policymakers and clinicians navigate through a complex and tangled web of diagnostic and therapeutic choices, patient preferences, and resource constraints to make optimal decisions? Medical interventions may have benefits but also adverse effects, e.g., surgery may lead to undesirable complications, and diagnostic technologies may produce false or inconclusive results.


    In many clinical and health policy decisions it is necessary to counterbalance benefits and harms and to trade off competing objectives such as maximizing life expectancy vs. optimizing quality of life vs. minimizing the resources required. In this course we will discuss a proactive approach to such decisions and discuss the basic concepts underlying decision analysis in order to integrate evidence and values for optimal and efficient care choices in the face of uncertainty. Topics include diagnostic reasoning, test interpretation, treatment thresholds, test-treat thresholds, estimating life expectancy, quality of life assessment, health technology, decision models and cost-effectiveness analysis.


    Teaching methods: Interactive lectures, exercises and practicums.

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    12 Aug 2019 - 16 Aug 2019
    Causal Inference [ESP48]

    About this course

    Faculty: Prof. Miguel Hernán, MD & Prof. Uwe Siebert, MD, MPH, MSc, ScD


    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 investigator adjusts for all potential confounders in the analysis of a properly designed study.


    To eliminate the discordance between the causal goals and the associational methods in epidemiology, it is necessary to a) formally define causal concepts such as causal effect and confounding, b) identify the conditions required to estimate causal effects, and c) use analytical methods that, under those conditions, provide estimates that can be endowed with a causal interpretation. These so-called g-methods can be used under less restrictive conditions than traditional statistical methods. For example, g-methods allow one to estimate the causal effect of a time-varying treatment in the presence of time-varying confounders that are affected by the treatment.


    This course combines counterfactual theory and graph theory to present an integrated framework for causal inference from observational data, with a special emphasis on complex longitudinal data. The course presents the latest methodologic developments for the design and analysis of longitudinal studies. Specifically, the course will introduce the three g-methods (inverse probability weighting of marginal structural models; parametric g-formula; and g-estimation of structural nested models) in the setting of time-fixed treatments, and demonstrate inverse probability weighting for addressing causal questions regarding static and dynamic treatment strategies.

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    12 Jun 2019 - 12 Jun 2019
    Integration module [PU04]

    About this course

    Master students in Public Health will have to demonstrate their ability to integrate their knowledge and expertise into evidence-based advice for policy makers and practitioners. Based on the (draft) research paper the student will make a presentation of 10 minutes, addressing the following topics:

    • What is the problem addressed?- How does your study contribute to this problem?
    • How will your results impact population health?
    • What action should policy makers and professionals take?
    • These presentations will be followed by a discussion with faculty and fellow students. In addition, students are required to write a one page reflection on the courses in the programme.

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    11 Nov 2019 - 15 Nov 2019
    The Placebo Effect [MP02]

    About this course

    The placebo effect has been studied since the 1950’s, starting with the original 1955 study of Beecher. In this course we will discuss several postulated underlying mechanisms of the placebo effect (e.g. expectancy, conditioning, affect-modulation, and doctor-patient communication). Furthermore we will debate the existence of the placebo effect and discuss the challenges in measuring the effect. Questions that will be addressed are for instance: can you deliver an open label placebo? Is it ethical to prescribe a placebo when a patient doesn’t know he is getting a sugar pill? Does the placebo effect exist outside of pain medication research? You will experience the strength of the placebo effect first hand in an experiment during the course.

    The assessment of the course will exist of the presentation of a research proposal for studying the placebo effect.

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    11 Jun 2019 - 11 Jun 2019
    Site visit to the Municipal Health Service Rotterdam [PU03]

    About this course

    The site visit is a orientation on public health practice in the Netherlands. The visit will be to the Municipal Public Health Service of Rotterdam (GGD Rotterdam). The objective is to provide the participant with a brief insight on how the GGD is organized and which services are provided to the community. After the field visit the participant is able to describe the learning experience regarding the visit in a structured report and to compare the services provided by the GGD and the way that these services are implemented with public health services in the participant's country of origin or country of work.

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    06 May 2019 - 10 May 2019
    Advanced Decision Modeling [CE15]

    About this course

    This week-long, project-based course aims to provide students with an understanding of advanced methods used in decision-analytic modeling and cost-effectiveness analyses. These include topics like the latest methods for calibration and validation, quantifying uncertainty, and consideration of heterogeneity of patient benefits and equity issues. The course combines lectures and readings to give theoretical foundation and perspectives with in depth project work and presentations to give practical concrete understanding in a way that furthers students’ specific research goals.

    Course Structure: Each day will begin with a lecture by Professor Goldhaber-Fiebert on an advanced methods topic. After the lecture, lab sessions will commence with students working on their projects as Professor Goldhaber-Fiebert circulates through the room and students assist each other in a collaborative environment. Most days Professor Goldhaber-Fiebert will also give an afternoon lecture. In addition, at the end of days 2, 3, and 4, Professor Goldhaber-Fiebert will give an additional, shorter, informal lecture (i.e., "a chalk talk") on a methods topic tailored to specific issues that are arising within students’ projects. Additionally, throughout the week, Professor Goldhaber-Fiebert will have one-on-one meetings with students about their projects.

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    06 May 2019 - 10 May 2019
    Biostatistical Methods I: Basic Principles Part A [CC02A]

    About this course

    The analysis of collected data is an inevitable part of almost any medical research project. Consequently, knowledge of and insight in the basic principles of data-analysis are essential for medical researchers. The course CC02 - Biostatistical Methods I: basic principles is designed to teach classical and basic statistical techniques for the analysis of medical research data. The course comprises lectures as well as computer practicals, in which students will apply the widely used statistical software packages SPSS and/or R to work through exercises.

    CC02 consists of two parts. In part A, which lasts one week, basic applications of biostatistics will be introduced, including descriptive statistics, general principles of statistical hypothesis testing, statistical inferences on means and proportions, and interval estimates for association measures.

    During the lectures, time will be spent on practical examples and exercises. Throughout the course, examples of SPSS- and R-programmes and -output will be demonstrated in relation to the topics that will be discussed.

    Biostatistical Methods I: Basic Principles, part A (CC02A) is equivalent to Introduction to Data-analysis (ESP03) and Biostatistics for Clinicians (EWP22).

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    05 Aug 2019 - 23 Aug 2019
    Review of Mathematics and Introduction to Statistics [BST01]

    About this course

    Several courses in the NIHES curriculum require a good working knowledge of basic concepts in mathematics and statistics. These courses include Biostatistical Methods I: Basic Principles (CC02), Biostatistical Methods II: Classical Regression Models (EP03), Repeated Measurements (CE08) and Bayesian Statistics (CE09). The course "BST01: Review of Mathematics and Introduction to Statistics" aims to prepare you for these statistical courses by helping you to obtain a sufficient working knowledge of mathematics and statistics. This course is a self-study course based on online material (videos from external sources) and the material in an accompanying reader. There will be no lectures or tutorials, but the organizers of the course are available for questions during the course. A number of exercises and a practice test are included in the course materials. The content of this course is divided into the following topics:

    • Basic mathematical operations
    • Functions
    • Differentiation
    • Integration
    • Vectors and matrices
    • Basic concepts in statistics

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    05 Aug 2019 - 09 Aug 2019
    Principles of Research in Medicine and Epidemiology [ESP01]

    About this course

    Faculty: Prof. Arfan Ikram, MD PhD


    This course will provide an orientation to medical research from a quantitative and epidemiological viewpoint. The course will give an introduction to the design of clinical and public health research, and it will discuss measures of disease frequency and association, and the validity of research in medicine. It will give an overview of elements of data-analysis.

    Teaching methods:
    Interactive lectures, exercises, practicals

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    05 Aug 2019 - 09 Aug 2019
    Introduction to Data-analysis [ESP03]

    About this course

    Faculty: Prof. Adelin Albert, PhD


    This course is a general introduction to the basics of statistics used in biomedical and public health applications. We start with a general definition of statistics and give some examples. We then review the notions of population, sample, variables (qualitative and quantitative) and data (missing, outlying, and censored). Next, the course focusses on ways to describe data such as tables, graphs, distributions and summary statistics (mean, standard deviation, median, quartiles) as reported in medical journals. Lifetime data will be visualized graphically by the celebrated Kaplan-Meier survival curve. Association measures between variables (correlation, regression, relative risk, odds ratio and hazard ratio) as well as agreement measures between observers (Cohen kappa coefficient) will be discussed.

    The course will then turn on the relation between the population and the random sample and on how characteristics observed in the sample can be generalized to the population. Some elementary probability elements will be needed here. This will lead to the important concepts of standard error and confidence intervals (for means, proportions, odds ratios, hazard ratios). The general theory of hypothesis testing will be briefly outlined from an intuitive perspective and the fundamental concepts of statistical significance, power calculation and p-value will be introduced. Then, we shall review some of the most frequently used testing procedures: correlation test, unpaired and paired t-tests for comparing two means values, analysis of variance for comparing several means (with multiple tests correction), chi-squared test (Fisher exact test) for comparing two proportions and more generally for contingency tables, McNemar test for paired proportions, and two-way analysis of variance for repeated data. The logistic model and Cox model will be briefly alluded to because of their importance in the medical literature. Finally, the basic principles underlying non parametric tests will be outlined and some of the most used distribution-free tests presented (Spearman correlation, Wilcoxon signed rank test, Mann-Whitney U-test, Kruskal-Wallis and Friedman tests).

    During the course, a brief introduction to the R statistical software will be given to participants. R is free of charge, increasingly used worldwide, but not easy to learn for the layman due to its tedious programming language. There is however a 'Point-and-Click' interface for R called the 'R Commander' or simply 'Rcmdr' which is really easy to learn and use. Thus, students will acquire some familiarity with the R Commander, do basic statistical calculations and draw nice graphs even on large datasets.

    Topics covered in the course will be illustrated using real data from the medical literature. Participants will also use Rcmdr during the course.

    Written exam on the Friday in the week after ESP (only for NIHES MSc students and for ‘keuzevak students’). Course materials are allowed during the examination. If other students wish to do this exam, they have to pay a fee of €75,- per exam. Credits are 1.0 ECTS when you take the exam, instead of 0.7 ECTS. Please contact NIHES (nihes@erasmusmc.nl) if you wish to register for the exam, at least two weeks before the start of the course.

    This course is equivalent to Biostatistics for Clinicians (EWP22) and Biostatistical Methods I: basic principles, part A (CC02A).

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    05 Aug 2019 - 09 Aug 2019
    Clinical Trials [ESP14]

    About this course

    Faculty: Prof. Marcel Zwahlen, PhD and Sven Trelle, MD, MSc


    This basic and intermediate level course covers design, conduct and analysis issues of clinical trials. We will discuss the clinical, scientific, and regulatory aspects of clinical trials, which investigate the efficacy and safety of candidate treatments or of diagnostic procedures. We will cover issues regarding the design such as the identification of the target population, choice and definition of the intervention and the comparators, choice and definition of study outcomes and assumptions needed to determine the size of the trial. Regarding the conduct and implementation of clinical trials we will cover the need for trial registration, choice of randomization strategies and procedures, the role of blinding, issues on prevention and handling of missing data, monitoring of the study, and the standards for the reporting of the trial results. Throughout the course emphasis is placed on pre-specification of these elements in a well-defined study protocol and on documentation of implementation and conduct of the study.


    Teaching methods:

    Lectures and group work on critical appraisal of published clinical studies with a focus on randomized trials.

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    05 Aug 2019 - 09 Aug 2019
    Topics in Meta-analysis [ESP15]

    About this course

    Faculty: Prof. Matthias Egger, MD MSc FFPH and Prof. Marcel Zwahlen, PhD


    Programme

    Introductory lecture: Why do we need systematic reviews and meta-analyses?

    Lecture / pen and paper practical: Measures of association

    Lecture: Basic statistical methods


    Computer practical

    Basic meta-analysis in Stata

    Lecture / demonstration: Identifying relevant studies

    Practical: Identifying relevant studies in PubMed


    Lecture Assessing quality and risk of bias

    Lecture The scope of meta-analysis: Meta-analysis of observational studies

    Case study / group work: How good is this meta-analysis?

    Case study / group presentations How good is this meta-analysis?

    Lecture Explaining heterogeneity and detecting bias

    Lecture / case study Individual participant data (IPD) meta-analysis


    Lecture Meta-analysis of dose-response relationships in epidemiology

    Computer practical Advanced meta-analysis in Stata I & II

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    05 Aug 2019 - 09 Aug 2019
    Introduction to Global Public Health [ESP41]

    About this course

    Faculty: Rajiv Chowdhury, MD PhD


    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 populations in the changing global context.


    Some of the specific health issues to be discussed include: the global rise of the non-communicable diseases (NCD) such as cardiovascular disease and diabetes; threats to health from pre-existing and emerging communicable diseases; maternal and child health issues, and the impact of global environmental change. Additionally, other related issues such as concepts and realities of health systems around the world, impact of globalization on health, and how to measure global health will be discussed. For each health problem, where appropriate, there will be a discussion of: burden of disease, major determinants, intervention policies and programmes, and evaluation of the effectiveness of the interventions. A key focus of the course would be small group interactions.

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    05 Aug 2019 - 09 Aug 2019
    Principles of Genetic Epidemiology [ESP43]

    About this course

    Faculty: Prof. Cornelia van Duijn, Ir. PhD

    This course aims to give a basic introduction to various methods used in classical genetic epidemiology. In combination with the course Genomics in Molecular Medicine and Genome Wide Association Studies, the course offers an excellent introduction to genetic epidemiologic research. The course targets epidemiologists, clinicians and molecular biologists with no background in genetic epidemiology. Participants are introduced to the basic principles of population genetics, segregation, linkage and association analyses. The relevant background of human genetics and statistics is presented. The goal of the course is that participants are able to interpret the findings in modern genetic research.

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    05 Aug 2019 - 09 Aug 2019
    History of Epidemiologic Ideas [ESP53]

    About this course

    Faculty: Prof. Alfredo Morabia, MD PhD


    This is a methodology course, which focuses on the historical evolution of methods (e.g., study designs) and concepts (e.g., confounding, bias, interaction and causal inference) that constitute today’s epidemiology. For each topic, we review and discuss the historical contexts and some landmark studies that led to specific innovations in terms of performance of group comparisons, population thinking and framing of hypotheses. We finally discuss the historical conditions for the emergence of epidemiology as a scientific discipline, the phases it went through and its potential, future developments.

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    05 Aug 2019 - 09 Aug 2019
    Markers and Prediction Research [ESP62]

    About this course

    Faculty: Prof. John Ioannidis, MD DSc & Maryam Kavousi, MD PhD


    Prognostic research is of growing importance, as globally more people are living with disease and clinicians and policy makers seek ways of targeting existing treatments and improving health outcomes. There is a rapid expansion in the number of new prognostic markers. Often, bold claims are made about their potential to assist in personalising approaches to medical care and treatment. Prognostic models may be useful to summarize the effects of multiple predictors but while commonly developed, such models are often not well validated or used in clinical practice.


    This course aims to provide the basic knowledge and principles to evaluate the quality of prognostic research and its translation to inform decision making of clinicians and policymakers. Drawing on recent examples and current controversies in cardiovascular disease, cancer, trauma and other conditions, the course examines molecular biomarkers and genetic variants through to the quality of healthcare as predictors of outcome. Topics include design, conduct and analysis of prognostic research; outcomes research; prognostic factors and prognostic markers; prognostic models for risk prediction; and stratified and personalised medicine.


    There will be lectures, interactive debates and critical appraisal of papers, but no computer labs (the course does not cover advanced statistical methods, see Further reading).

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    05 Aug 2019 - 09 Aug 2019
    Logistic Regression [ESP66]

    About this course

    Faculty: Prof. Stanley Lemeshow, PhD


    This course provides theoretical and practical training for biostatisticians, epidemiologists and professionals of related disciplines in statistical modeling with particular emphasis on logistic regression. The increasingly popular logistic regression model has become the standard method for regression analysis of binary, multinomial and ordinal response data in the health sciences.

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    05 Aug 2019 - 09 Aug 2019
    Advances in Clinical Epidemiology [ESP77]

    About this course

    Faculty: Prof. Albert Hofman, MD PhD

    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 discussed. The application of novel causal inference methods and the use of instrumental variables will be addressed.

    The course includes both didactic interactive lectures as well as discussions and workshops. The workshops will provide the opportunity to discuss, in greater depth, the principles covered in the lectures.


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    04 Nov 2019 - 08 Nov 2019
    Public Health Research: Intervention Development and Evaluation [HS02c]

    About this course

    Public Health Research: from Epidemiology to Health Promotion

    Module: Intervention Development and Evaluation.

    This module elaborates on the intervention development, implementation and evaluation phases in the model of planned promotion of public health.

    Students will:

    • be introduced to strategies and opportunities of primary and secondary prevention;
    • learn how to work from determinants to interventions, i.e. how to translate determinants into intervention goals and intervention components and;
    • learn about the opportunities and challenges of evaluation of primary and secondary prevention interventions and;
    • be introduced to theory and challenges in dissemination of prevention interventions.

    The course uses examples from health behaviour change, cancer screening, and vaccination.

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    03 Jun 2019 - 05 Jun 2019
    Cardiovascular Epidemiology [EP20]

    About this course

    Cardiovascular disease remains the leading cause of morbidity and mortality worldwide. The overall objective of the cardiovascular epidemiology course is to produce epidemiologists and other health scientists with the essential knowledge to carry out high quality research in cardiovascular disease.

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