Find your programme or course by following the steps

Step 1/4:

I am looking for a …

Programme

Choose

Course

Choose

Step 2/4:

My research background:

I have no research experience

Choose

I have research experience

Choose

Step 3/4:

I am interested in the following discipline:

Epidemiology

Choose

Clinical Epidemiology

Choose

Genetic Epidemiology

Choose

Public Health

Choose

Pharmaco Epidemiology

Choose

Health Economics

Choose

Clinical Research

Choose

No specific interest

Choose

Step 4/4:

I am interested in following a programme:

Full-time

Choose

Part-time

Choose

Step 2/4:

I am interested in the following discipline:

Advanced Statistics

Choose

Biostatistics

Choose

Clinical Epidemiology

Choose

Clinical Research

Choose

Epidemiology

Choose

Genetic Epidemiology

Choose

Health Economics

Choose

Methodology

Choose

Pharmaco Epidemiology

Choose

Public Health

Choose

Step 3/4:

I am looking for a course on this level:

Basic

Choose

Intermediate

Choose

Advanced

Choose

Step 4/4:

I want to follow a course in this time-frame:

Summer (July August September)

Choose

Autumn (October November December)

Choose

Winter (January February March)

Choose

Spring (April May June)

Choose

Your result based on your answers

Didn't find what you were looking for?

Try again!

Programme overview (based on your choices)

Programmes & specializations videos

PhD Programme | 4 Years | FULL-TIME

For whom?

This content of this programme will be published soon. Our apologies for the inconvenience. Please contact our office if you wish to receive further information about this programme.

Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Pharmaco Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • 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
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Senior Advanced PhD Programme

    For whom?

    The content of this web page is currently under construction. Our apologies for the inconvenience. Please contact our office if you wish to receive further information about this programme.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Pharmaco Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • 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.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Pharmaco Epidemiology
  • Biostatistics
  • Medical Psychology
  • 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.

    Read More

    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.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Health Economic Analysis
  • Doctorate

    PhD Programme | 4 Years | FULL-TIME

    For whom?

    This content of this programme will be published soon. Our apologies for the inconvenience. Please contact our office if you wish to receive further information about this programme.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Pharmaco Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • 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
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Senior Advanced PhD Programme

    For whom?

    The content of this web page is currently under construction. Our apologies for the inconvenience. Please contact our office if you wish to receive further information about this programme.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Pharmaco Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • 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.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Pharmaco Epidemiology
  • Biostatistics
  • Medical Psychology
  • Courses

    29 Oct 2018 - 02 Nov 2018
    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.

    Read More

    28 Nov 2018 - 06 Feb 2019
    Scientific Writing in English for Publication [SC07]

    About this course

    Course days in 2017-2018 will be:Wednesday November 22, Wednesday December 13, Monday January 15 and 29.The first 3 sessions will be on mornings or afternoons depending on your group.

    The last session on the 29th will be in the morning, afternoon or evening depending on your group and other course schedule.


    Writing to be read

    This course will focus on:

    • Communicating the point and importance of your research;
    • Writing a clear and readable scientific article.The course consists of 4 half-day sessions and 3 writing assignments that will receive individual feedback from the instructor as well as other course participants. Attending all 4 sessions and completing all writing assignments is compulsory.

    The course will be intensive—writing takes time—so we suggest that participants reserve considerable time for this course.

    Participants will be guided through the writing process in 3 assignments:

    1. Clarifying the point of the research;
    2. Completing the Hourglass Template with the main messages for the Introduction, Methods, Results, and Discussion of your research;
    3. Writing the Abstract and Title.

    Part of the work will be peer reviewing. Participants will critically discuss each of the three assignments with a peer-review partner (i.e. another course participant). The remaining members of the peer-review group will review and critique each assignment as well. This implies that participants must be willing to work closely with a peer-review partner during the course and meet deadlines for peer reviewing. After revising texts based on these reviews, participants then send them to the instructor, who will provide both substantive and language tips.

    Read More

    28 Jan 2019 - 01 Feb 2019
    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. 

    Read More

    27 Aug 2018 - 14 Sept 2018
    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.

    Read More

    25 Oct 2018 - 09 Nov 2018
    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

    Read More

    25 Mar 2019 - 29 Mar 2019
    Planning and Evaluation of Screening [HS05]

    About this course

    This course focuses on the design and the evaluation of health care programmes for the early detection of disease or screening. Screening takes place in a population without symptoms of the disease. The screening test characteristics have consequences for the favourable (improvement of prognosis by early detection, life years saved and deaths prevented) and unfavourable (overdiagnosis, unnecessary treatments) effects of screening.


    There are a number of designs for the assessment of the effectiveness of screening, such as randomized-controlled trials, observational prospective studies and case control studies. The pros and cons of each of these designs will be discussed. Evaluation methodologies, such as cost-effectiveness, cost-utility and technology assessment will be explained, including the concepts of quality adjustment of life years and of time preference. Detailed case studies include cervical, breast and prostate cancer screening, genetic screening, youth health care and screening for tuberculosis, e.g. for high risk groups. Several computer aids for the evaluation of screening are presented.

    Read More

    22 Oct 2018 - 26 Oct 2018
    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

    21 Jan 2019 - 25 Jan 2019
    Pharmaco-epidemiology and Drug Safety [EWP03]

    About this course

    Pharmaco-epidemiology plays a role of increasing importance in the field of drug safety and regulatory decision making. On the one hand, the introduction of computers into clinical practice facilitates the performance of large-scale cohort studies and nested case-control studies. On the other hand, it creates some problems regarding the quality of outcome and exposure assessment. Because the commercial consequences of pharmaco-epidemiological studies may be enormous, discussions in this area may be heated.


    In this course, referring to established drug safety problems will highlight some of the complex aspects of outcome and exposure assessment in pharmaco-epidemiology.


    Teaching Methods

    Plenary teaching as well as computer exercises on the analysis of cohort- and case-control data.

    Read More

    20 Aug 2018 - 24 Aug 2018
    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.

    Read More

    20 Aug 2018 - 24 Aug 2018
    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.

    Read More

    20 Aug 2018 - 24 Aug 2018
    Social Epidemiology [ESP61]

    About this course

    Faculty: Prof. Frank van Lenthe, PhD & Prof. Johan Mackenbach, MD 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.

    Read More

    20 Aug 2018 - 24 Aug 2018
    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.

    Read More

    20 Aug 2018 - 24 Aug 2018
    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

    20 Aug 2018 - 24 Aug 2018
    Workshop Advanced Medical Writing and Editing [ESP71]

    About this course

    Faculty: Prof. Philip Greenland

    The hands-on course, taught more as a workshop than a lecture course, should be of benefit to anyone interested in improving medical writing skills and in more effectively understanding the biomedical publication process. Students will refine and demonstrate writing, reading, editing, and reviewing skills. Discussion areas include: How journal editors think and make decisions, what matters (impact factor), what/how to prepare before writing, ethics of authorship, and understanding the peer review process. This course is designed to improve medical writing skills for those who already have some experience in medical writing, including those with moderately extensive experience.

    • How journal editors and reviewers reach decisions about articles - what is important?
    • What matters - Impact Factor?
    • Editorial Ethics: Who is an author? What else is important?
    • What and how to prepare before you write
    • Learning by doing peer review
    • Learning to do an outline before writing
    • All the basics for submission: Cover letter, Title page, Abstract, Introduction, Methods, Results, Tables, Figures, References, Acknowledgements, Supplementary Material

    In the first of the 5 class sessions, we will extensively review several articles as a background for improving one’s own recognition of common writing mistakes. In the remaining sessions, we will cover the following topics:

    • Improving titles and abstracts;
    • Preparing an outline before writing a paper – why this is a good idea and how to do it;
    • Discussions of papers in progress by members of the class;
    • Preparing a response to a review – how to be successful in getting your nearly accepted paper to the finish line.

    Each student should be actively writing a paper or willing to share a recently completed paper to be used for discussion within the class.

    It is strongly encouraged that students submit papers-in-progress to the professor before the course begins since these can be used for class discussions.

    Class members will be expected to take part in active discussion, and are encouraged to do approximately one hour of reading and up to 1-2 hours of writing each day before class, and to submit a paper for review before the class begins on August 20.

    Teaching methods: There will be readings for each class and some writing assignments between classes. The class depends on very active participation in analyzing papers, writing outlines, titles, abstracts, and responses to reviews. While there will be some degree of "lecturing" from the professor, the class is primarily designed for active learning by the students rather than learning from lecture.

    Important Request

    This class will utilize written work for workshop analysis. It is desirable, and preferred, to utilize actual written materials prepared by members of the class. Please send to Professor Greenland, in advance of the class, at least one paper that you are currently working on, or a paper currently under peer review, or even an outline of a paper that you are proposing. Wherever possible, workshop discussions will be based upon actual writing from members of the class. Please participate!!!

    Read More

    20 Aug 2018 - 24 Aug 2018
    Genome-wide association studies [ESP74]

    About this course

    Faculty: Prof. Cornelia van Duijn, Ir. PhD & 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.

    Read More

    20 Aug 2018 - 24 Aug 2018
    Human Epigenomics [ESP75]

    About this course

    Faculty: Jordana Bell, PhD and Elena Carnero-Montoro, 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.

    Read More

    20 Aug 2018 - 24 Aug 2018
    Value Based Healthcare, from theory to implementation [ESP76]

    About this course

    Faculty: Prof. Jan Hazelzet, MD PhD, Dr. Tom Kelley, MD MBA & Dr. Rishi Hazarika, MBBS BSc


    Overall aim: To provide participants an overview of all aspects of value-based-health care (VBH) as theorised by Prof Michael Porter, Harvard Business School. Where value is defined as the outcomes achieved for patients relative to costs. Using the case based method of teaching and incorporating practical examples of how leading health care organisations have followed VBH principles and implemented and utilised outcome measurement to aid clinical practice and patient led decision making. The programme consists of 15 lectures and will deal with all the aspects of value based healthcare.

    Read More

    20 Aug 2018 - 23 Aug 2018
    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.

    Read More

    19 Nov 2018 - 07 Dec 2018
    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.

    Read More

    18 Mar 2019 - 21 Mar 2019
    Psychiatric Epidemiology [EP12]

    About this course

    This four-day course focuses on the principles and practice of psychiatric epidemiology. Basic concepts and issues that are specific to both child and adult psychiatric epidemiology are covered. Psychiatric issues that will be used to illustrate concepts and practice of psychiatric epidemiology include: prevalence studies, longitudinal studies, the role of risk and resilience, and genetic epidemiology. Invited speakers will cover particular topics such as migration and psychiatirc disorder, the epidemiology of bipolar disorder, schizophrenia and addiction in more detail.Maximum 40 participants.


    Read More

    18 Mar 2019 - 22 Mar 2019
    Survival Analysis for Clinicians [EWP24]

    About this course

    Survival analysis is the study of the distribution of life times, i.e. the times from an initiating event (birth, diagnosis, start of treatment) to some terminal event (relapse, death). Survival analysis is most prominently (but not only) used in the biomedical sciences. A special feature of survival data is that it takes time to observe the event of interest. A result of this seemingly innocent observation is that for a number of subjects the event is not observed, but instead it is known that it has not taken place yet. This phenomenon is called censoring and it requires special statistical methods. During the course different types of censored and truncated data will be introduced and techniques for estimating the survival function by employing both parametric and non-parametric methods will be illustrated. Also techniques for testing equality of survival functions (the log-rank test and alternatives) are discussed. Finally regression models for survival analysis, based on the hazard function (most notably the Cox proportional hazards model), will be studied in great detail. Special aspects such as time-dependent covariates and stratification will be introduced. Techniques to be used to assess the validity of the proportional hazards regression model will be discussed. The last part of the course touches on models for multivariate survival analysis, including competing risks and multi-state models and frailty models. Finally, aspects of the planning of clinical trials with lifetime data will be discussed.


    Teaching methods

    All aspects of the course will be illustrated with real data examples and will be practiced with computer practicals and/or pen-and-paper exercises.


    Survival Analysis (EWP24) is equivalent to the Survival Analysis course (ESP28) in the Erasmus Summer Programme and the part about survival analysis in  Biostatistical Methods II: classical regression models (EP03).

    Read More

    18 Feb 2019 - 22 Feb 2019
    Advanced Clinical Trials [EWP10]

    About this course

    The Randomized Controlled Clinical Trial (RCT) is the most reliable  method of assessing the efficacy and effectiveness of interventions. In order to provide the best possible evidence-based health care, health professionals must be able to judge the scientific merits and clinical relevance of published RCTs. In addition, they may be involved in designing and performing a RCT and are frequently asked to recruit patients for RCTs.

    Reports published in major medical journals show a surprising variability in methods including choice of study design, blinding, avoidance of bias, outcome measures, effect parameters, sample size calculations, data analysis techniques, presentation of results in tables and figures, and inferences made from the results. Hence, appraising trial reports can be challenging. In designing RCTs many difficult decisions need to be made with respect to these same issues.

    In this course these topics and issues will be addressed and developed through lectures and group practical sessions. A laptop during classroom sessions is required in order to do the practical assignments.


    Read More

    17 Oct 2018 - 09 Nov 2018
    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.

    Read More

    17 Sept 2018 - 12 Oct 2018
    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 package SPSS 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. SPSS will be introduced in the first week. Throughout the course, examples of SPSS-programmes and -output will be demonstrated in relation to the several 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).

    Read More

    15 Oct 2018 - 23 Oct 2018
    Clinical Translation of Epidemiology [CE01]

    About this course

    In the course, the principles and practice of clinical epidemiology will be considered and examples from the literature will be worked out and discussed. The aim is to provide the participants with the knowledge to evaluate and judge applied clinical research and data analysis and give a sufficient scientific and methodologic background to actively participate in clinical studies. 


    Topics are: principles of applied clinical research, diagnostic reasoning, diagnostic and prognostic research, comparative (clinical) experimental study, comparative non experimental study, meta-analysis and evidence based medicine.

    Read More

    15 Oct 2018 - 16 Oct 2018
    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

    15 Oct 2018 - 19 Oct 2018
    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!

    Read More

    15 Oct 2018 - 09 Nov 2018
    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.

    Read More

    13 Aug 2018 - 17 Aug 2018
    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).

    Read More

    13 Aug 2018 - 17 Aug 2018
    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.

    Read More

    13 Aug 2018 - 17 Aug 2018
    Conceptual Foundation of Epidemiologic Study Design [ESP38]

    About this course

    Faculty: Prof. Kenneth Rothman, DrPH


    This course elaborates the fundamental principles of epidemiologic study design. It begins with an introduction to the basic principles of epidemiologic inference, including concepts of causation, causal inference and the measurement of disease occurrence and causal effects. With this foundation, attention shifts to the principles of study design and discussion of the major types of epidemiologic study, primarily cohort and case-control studies. The utility and consequences of matching in subject selection is also addressed. The course concludes with a presentation of the underlying principles of epidemiologic data analysis.

    Read More

    13 Aug 2018 - 17 Aug 2018
    Cohort Studies [ESP39]

    About this course

    Faculty: Prof. Jonathan Samet


    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.

    Read More

    13 Aug 2018 - 17 Aug 2018
    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.

    Read More

    13 Aug 2018 - 17 Aug 2018
    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.

    Read More

    13 Aug 2018 - 17 Aug 2018
    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.

    Read More

    13 Aug 2018 - 17 Aug 2018
    Markers and Prediction Research [ESP62]

    About this course

    Faculty: Prof. John Ioannidis, MD DSc, Prof. Ewout Steyerberg, PhD & 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).

    Read More

    13 Aug 2018 - 16 Aug 2018
    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.

    Read More

    13 Aug 2018 - 17 Aug 2018
    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

    Read More

    13 Aug 2018 - 17 Aug 2018
    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.

    Read More

    13 Aug 2018 - 17 Aug 2018
    Joint Models for Longitudinal and Survival Data [ESP72]

    About this course

    Faculty: 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

    13 Aug 2018 - 17 Aug 2018
    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.


    Read More

    13 May 2019 - 17 May 2019
    Bayesian Statistics [CE09]

    About this course

    There is growing acknowledgement of the value of Bayesian methods for complex models in biostatistics and epidemiology, in dealing with issues such as multiplicity, measurement error, spatial associations and hierarchical structure. This course will introduce the essentials of Bayesian ideas, emphasizing practical application using exact and simulation-based software. Examples will include the use of Bayesian methods in clinical trials, institutional comparisons, smoothing of disease rates, and frailty models.

    Read More

    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.

    Read More

    13 Mar 2019 - 15 Mar 2019
    Quality of Life Measurement [HS11]

    About this course

    In recent years, the patient's assessment of quality of life has developed to an important outcome measure in epidemiology and health services research. Moreover, quality of life measures are increasingly used as criteria in reimbursement policy, most notably in QALY-analysis.

    The aim of the course is to provide the participants first, with a review of the instruments currently available; Second, participants are provided with the knowledge required to select measures of quality of life that are both valid and sensitive for the research objectives of the participants;

    Third, participants will acquire the knowledge and practical skills necessary to adjust standard measures of quality of life instruments for their specific disease area’s, with a special focus on reimbursement. The programme consists of presentations, exercises and demonstrations of practical issues. Participants are invited to email their specific interest at forehand, and these topic will be discussed during the course.

    Programme:

    • Background of ‘health status' and ‘quality of life’.
    • Main principles of construction of a quality of life questionnaire.
    • Available instruments.

    Application.

    • Adaptation instruments for specific research questions: increase sensitivity.
    • QALY-analysis.
    • Practical and ethical value of measuring quality of life in a reimbursement setting.

    Read More

    12 Nov 2018 - 16 Nov 2018
    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.

    Read More

    12 Nov 2018 - 16 Nov 2018
    SNPs and Human Diseases [GE08]

    About this course

    The analysis of DNA polymorphisms, in particular Single Nucleotide Polymorphisms (SNPs), is becoming a standard research approach to understand causes of disease, in particular the so-called "complex" diseases such as diabetes, osteoporosis, cancer, etc. The aim of this course is to give a broad introduction in SNP techniques and applications. 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:

    https://www.molmed.nl/

    Read More

    12 Nov 2018 - 16 Nov 2018
    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.

    Read More

    12 Nov 2018 - 16 Nov 2018
    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.

    Read More

    11 Feb 2019 - 15 Feb 2019
    Preventing Failed Interventions in Behavorial Research [MP05]

    About this course

    This course elaborates on intervention development, implementation and evaluation in the field of medical psychology. The focus is on learning from encountered difficulties, mistakes en failures from previous research and researchers. Questions that will be discussed are:

    • How to design an intervention taken into account both common and specific therapy factors?
    • How to evaluate the effectiveness of your intervention and not the effectiveness of the therapist?
    • How to motivate other professionals and institutions to cooperate in a multicenter trial?
    • How to prevent loss to follow-up and dropout?
    • How to prevent various biases in your outcome measures?
    • What is the best available outcome instrument for the intervention studied?
    • How to determine which elements of your intervention are most effective?
    • How to implement your intervention?

    Read More

    09 Apr 2019 - 11 Apr 2019
    Mendelian Randomisation [GE10]

    About this course

    This 3-day course aims to give an overview of recent developments in drawing causal inferences from epidemiological data using Mendelian randomization and is aimed at individuals with a background in statistics or epidemiology with a strong statistics component. Theoretical discussion will be accompanied by introduction to available software and lab practicals.


    The first day will comprise a brief introduction to graphical models since these provide a natural framework for expressing and manipulating many of the concepts involved. We will then go on to causal modelling and the need for a formal causal framework before explicitly considering instrumental variable methods with Mendelian randomisation applications as the primary example. 

    The second day will focus on various theoretical issues, together with their relevance to practical applications in terms of what can and what cannot be done. Bayesian approaches to Mendelian randomization will also be introduced.


    On the final day, current topics of interest including checking for violations of assumptions, the use of multiple instruments and implications for case-control data will be introduced.


    N.B.: This course is organised every other year.

    Read More

    08 Apr 2019 - 12 Apr 2019
    Epidemiology of Infectious Diseases [CE05]

    About this course

    Quantitative approaches play an important role in the understanding of the spread of infectious diseases and provide important tools for prevention. During the course, the basic notions that describe the mechanisms behind the spread of a disease will be introduced. Several examples of what can be learned from the use of quantitative models will be given.


    The relation between the specific characteristics of some infectious diseases and their spread will be exemplified, e.g. for tuberculosis, hepatitis, measles, influenza, AIDS. Only a basic level of mathematics is needed, and exercises will be given to practice the theoretical concepts.

    Topics covered are:

    • Important concepts and tools in modelling the spread of infectious disease.
    • Some important quantities related to the spread of infectious diseases (incidence, prevalence, cumulative incidence, incubation time, latent time, period of infectiousness); estimation of these quantities, with an example from the HIV epidemic.
    • Simulating large scale and small scale epidemics using the computer.
    • Basic reproductive number (R0) as central determinant of whether an epidemic develops.
    • Mode of transmission (e.g. airborne, sexual) in relation to the characteristics of spread.
    • Heterogeneous spread; the role of mixing between subgroups; contact patterns.
    • Molecular epidemiology as a new tool to monitor and model the spread of an infectious disease.


    Prevention programmes.

    • Vaccination strategies in relation to characteristics of the infectious disease.
    • Cost-effectiveness analyses of prevention and treatment.
    • Screening of pooled blood samples.

    Read More

    08 Apr 2019 - 12 Apr 2019
    Cancer Epidemiology [EP13]

    About this course

    Cancer is a major cause of morbidity and mortality in the developed world. The aim of this 5-day course is to provide an overview of the contributions of exogenous and endogenous factors to the risk of various cancers. The course starts with descriptive cancer epidemiology and an overview of current concepts of cancer development at the molecular and cell level. Subsequently, genetic and non-genetic risk factors for the most important cancers will be extensively discussed, as well as gene-environment interactions. Special attention will be given to risk factors for multiple primary cancers and recent results of chemo prevention studies. Although the emphasis of the course will be on etiologic factors, one session will specifically address time trends in cancer incidence, mortality and survival rates, followed by a discussion on whether or not we are winning the battle against cancer.

    Read More

    06 Aug 2018 - 24 Aug 2018
    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

    Read More

    06 Aug 2018 - 10 Aug 2018
    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

    Read More

    06 Aug 2018 - 10 Aug 2018
    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).

    Read More

    06 Aug 2018 - 10 Aug 2018
    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 works on critical appraisal of trial protocols and published trial results.

    Read More

    06 Aug 2018 - 10 Aug 2018
    Topics in Meta-analysis [ESP15]

    About this course

    Faculty: Prof. Matthias Egger, MD MSc FFPH and 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

    Read More

    06 Aug 2018 - 10 Aug 2018
    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

    Read More

    06 Aug 2018 - 10 Aug 2018
    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.

    Read More

    06 Aug 2018 - 10 Aug 2018
    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.

    Read More

    06 Aug 2018 - 10 Aug 2018
    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.

    Read More

    06 Aug 2018 - 10 Aug 2018
    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.

    Read More

    06 Aug 2018 - 10 Aug 2018
    Causal Inference [ESP48]

    About this course

    Faculty: Prof. Miguel Hernán, MD & Sonja Swanson, 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.

    Read More

    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 package SPSS to work through exercises.


    In CC02 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. SPSS will be introduced. Throughout the course, examples of SPSS-programs and -output will be demonstrated in relation to the several topics that will be discussed.


    The courses Introduction to Data-analysis (ESP03) and Biostatistics for Clinicians (EWP22) are equivalent to Biostatistical Methods I: basic principles, part A (CC02A).

    Read More

    05 Mar 2019 - 08 Mar 2019
    Principles of Epidemiologic Data-analysis [EWP25]

    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.


    Teaching Methods

    The course consists of lectures, case studies involving reading and classroom discussion, and assignments using a spreadsheet for epidemiologic data analysis, which is supplied.

    Read More

    04 Feb 2019 - 08 Feb 2019
    Family-based Genetic Analysis [GE05]

    About this course

    The course focuses on theoretical background and practical issues in the genetic analysis of complex traits. It considers two main gene-finding approaches: model-free linkage studies, and pedigree-based association analyses. It also addresses the analysis of qualitative outcomes - such as diseases - and quantitative (or continuous) traits.


    As well as maximum-likelihood estimation and Haseman-Elston methods for model-free linkage analysis, we will also cover issues such as extreme sampling, the inclusion of covariates, and the generalization of methods based on sibling pairs to other pedigree structures.


    Family-based association studies will be explored in the context of candidate genes and whole-genome association analysis. Various methods will be considered, including Transmission Disequilibrium-like tests, total tests that use between-family and withinfamily variation, and testing for maternal genotypeand parent-of-origin effects.

    Read More

    04 Feb 2019 - 08 Feb 2019
    Psychopharmacology [MP03]

    About this course

    Medical psychology is all about the interaction between mind and body: how do physical complaints affect our psychological functioning? But also: how does our psychological functioning affect us physically? When dealing with this interaction in a clinical setting, drug treatments often play an important role. Patients receiving drug treatment for psychiatric disorders frequently suffer physical side-effects, and drugs prescribed for somatic disorders can influence our mental state.


    Therefore, medical psychologists need to know which drugs are prescribed for common psychiatric and somatic disorders, and need to have a basic understanding of how these (psychoactive) drugs work, how and why they invariably lead to side-effects, and how these side-effect affect compliance. We will look at drug treatment for psychiatric disorders such as depression and schizophrenia, but also at drugs like corticosteroids – used in the treatment of somatic conditions such as inflammatory bowel disease – which have been found to increase the risk of suicidal behavior and neuropsychiatric disorders (i.e. depression, panic and manic episodes).

    Read More

    01 Apr 2019 - 05 Apr 2019
    Repeated Measurements [CE08]

    About this course

    This course covers statistical methods to be used when one or more variables are repeatedly measured in time on the same experimental unit. For instance, in a clinical trial, the outcome variable can be measured at baseline and at different times during the treatment period. In a meta-analysis, the study can be regarded as the experimental unit and the observations of patients within the same study as repeated measurements.


    In the last 10 or 15 years much progress has been made in the development of new methods of analysis. In recent years several of these new methods have been implemented in a wide variety of computer packages.


    The course starts with a short overview of simple methods for analyzing repeated measurements data, followed by a short recap of the most basic concepts of linear algebra needed for the presentation of the most advanced models.


    Then the main focus turns on more advanced methods. For approximately normally distributed repeated measurements outcomes marginal and linear mixed models are introduced. For non-normal responses, first the generalized estimating equations (GEE) approach for marginal inferences is presented, followed by extensions of random effects models to categorical outcomes. All these methods are exemplified using data from of clinical and epidemiological studies.


    Computer practicals in the statistical programming language R will be used to acquire hands on experience in applying these techniques to real data. All code used during the course will be live demonstrated using a web app, which will be made avaliable to participants.


    Participants need to bring their own laptop with certain pre-installed software (instructions will be given before start of the course). The assignment for this course needs to be handed in two weeks after the ending of the course on Friday April 27 2018.

    Read More

    Erasmus Winter Programme (EWP)

    For more information about the Erasmus Winter Programme (EWP), please go to:

    See overview of all available courses