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Programme overview (based on your choices)

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 ECTS

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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Specialisations

  • Epidemiology
  • Clinical Epidemiology
  • Genetic Epidemiology
  • Public Health
  • Pharmaco Epidemiology
  • Medical Psychology
  • Biostatistics

Research Master in Clinical Research | 2 Years | FULL-TIME | 120 ECTS

For whom?

There is a great need for clinicians who can combine patient care and research. This Research Master programme is a unique opportunity for medical students to become clinical investigators and pursue an academic career simultaneously.

This programme for ambitious students with a Bachelor degree in Medicine or Biomedical Sciences. 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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Research Master in Health Sciences | 2 Years | FULL-TIME | 120 ECTS

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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Specialisations

  • Genetic Epidemiology
  • Epidemiology
  • Clinical Epidemiology
  • Public Health
  • Health Economic Analysis
  • Medical Psychology

Doctorate

Doctor of Science 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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Specialisations

  • Epidemiology
  • Clinical Epidemiology
  • Genetic Epidemiology
  • Public Health

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.

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Specialisations

  • Epidemiology
  • Clinical Epidemiology
  • Genetic Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • Pharmaco Epidemiology
  • Public Health

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.

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Specialisations

  • Clinical Epidemiology
  • Epidemiology
  • Genetic Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • Pharmaco Epidemiology

Executive Education

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

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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Specialisations

  • Epidemiology
  • Genetic Epidemiology
  • Clinical Epidemiology
  • Pharmaco Epidemiology
  • Public Health

Courses

06 Mar 2017 - 10 Mar 2017
Advanced Analysis of Prognosis Studies [EWP13]

About this course

Prognostic models are increasingly published in the medical literature each year. But are the results relevant for clinical practice? What are the critical elements of a well developed prognostic model? How can we assume that the model makes accurate predictions for our patients, and not only for the sample that was used to develop the model (generalizability, or external validity)?

In the course we will address these and other questions from a methodological perspective, using examples from the clinical literature.
The participants will be encouraged to participate in interactive discussions and in practical computer exercises.

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06 Mar 2017 - 10 Mar 2017
Advanced Topics in Decision-making in Medicine [EWP02]

About this course

This course deals with advanced topics in clinical decision making. We will discuss a proactive systematic approach to decision making in health care and review the principles of cost-effectiveness analysis. Special topics that will be addressed include problems with utility assessment and multi-attribute utility theory, cost-analysis, modeling issues, Markov process models, Monte Carlo simulation modeling, and Value of Information analysis. The course will consist of lectures in the morning and a computer practicum in the afternoon.

During the week you will be given the opportunity to work on an own case example. Think of a decision problem that you are currently involved in or were recently confronted with. It may be a clinical decision problem involving a patient you care for, a management decision problem you are struggling with, a public health policy problem you are involved with, or a personal (preferably medical) decision problem. It must, however, be something you are willing to talk about in class and are motivated to work on.

Teaching Methods
9:00-12:00: Interactive lectures
13:00-16:00: Computer lab: Computer assignments and work on own case example with help from teaching assistants and the lecturer.

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06 Mar 2017 - 10 Mar 2017
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.

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13 Mar 2017 - 26 Apr 2017
Scientific Writing in English for Publication [SC07]

About this course

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.

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20 Mar 2017 - 24 Mar 2017
Courses for the Quantitative Researcher [SC17]

About this course

The aim of this course is to prepare NIHES MSc students for the more advanced statistical courses (i.e., Repeated Measurements, and Survival Analysis in the Erasmus Winter Programme,Bayesian Statistics, Missing Values in Clinical Research and Growth Models) by equipping them with the required knowledge of basic statistical concepts and statistical software.

The course consists of three parts:
- Basic concepts in mathematics and statistics;
- Introduction to the R statistical software and
- A brief introduction to the SAS language.

The first part covers essential concepts in statistics such as density and distribution function, types of distribution functions, integral calculations, differentiation, notions of matrix theory, optimization topics applied to likelihood and sampling. The second part, which is done in conjunction with the first one, introduces the R programming language that is used to perform data manipulations, graphics and statistical analyses. In the third part a brief introduction will be given of the SAS package with an emphasis on basic data manipulations.

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27 Mar 2017 - 31 Mar 2017
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.

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27 Mar 2017 - 30 Mar 2017
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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03 Apr 2017 - 07 Apr 2017
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.

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03 Apr 2017 - 07 Apr 2017
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?

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03 Apr 2017 - 07 Apr 2017
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).

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03 Apr 2017 - 30 Jun 2017
Identifying Susceptibility for Adverse Drug Reactions [D4M3]

About this course

For up-to-date course information please check:
http://www.eu2p.org/course-catalogue/medicines-risk-identification-and-quantification/identifying-susceptibilityfor-adverse-drug-reactions

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10 Apr 2017 - 14 Apr 2017
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.

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03 May 2017 - 05 May 2017
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.

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09 May 2017 - 11 May 2017
Maternal and Child Health [HS09]

About this course

The health of women of child bearing age and of children have an important impetus on public health. The aim of the course is to provide an insight into child health from conception onwards.

Determinants of fecundity, pregnancy and pregnancy outcome are discussed as a prerequisite for child health. Perinatal and infant mortality in an international perspective, growth and development are discussed as important health indicators. Preventive interventions such as vaccinations, screening programmes and health promotion are discussed. Special attention is given to the health of groups at risk for health problems such as children of low socio-economic classes and children of ethnic minorities. Psychosocial health problems are said to be on the increase. Facts and figures in an international perspective will be presented. In adolescence, life style habits are developed and appropriate health promotion is important. Examples of health promotion programmes are discussed. The programme consists of presentations, exercises and group discussions.

Topics covered:
- Determinants of fecundity, pregnancy and pregnancy outcome.
- Perinatal and infant mortality.
- Growth and development preventive interventions.
- Psycho-social health problems.
- The health of groups at risk.
- Adolescence and health promotion.

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

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15 May 2017 - 17 May 2017
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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19 May 2017 - 09 Jun 2017
Introduction to Medical Writing [SC02]

About this course

During the second semester, full time Master of Science students will attend three 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 work on his or her own article, which the teacher will correct.

Students from institutes participating in of affiliates with NIHES, including PhD candidates at Erasmus MC, do not attend SC02; they could consider the Erasmus Summer Programme course: 'Why and How of Readable Articles'.

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29 May 2017 - 29 May 2017
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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30 May 2017 - 02 Jun 2017
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.

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30 May 2017 - 01 Jun 2017
Missing Values in Clinical Research [EP16]

About this course

Missing data frequently occur in clinical trials. 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 longitudinal clinical trial data include complete-case (CC) analysis and an analysis using the last observation carried forward (LOCF). However, these methods rest on strong and unverifiable assumptions about the dropout mechanism. Over the last decades, a number of longitudinal data 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). 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.

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06 Jun 2017 - 06 Jun 2017
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 objectiveis 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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12 Jun 2017 - 16 Jun 2017
An Introduction to the Analysis of the Next-generation Sequencing Data [GE13]

About this course

This course provides an introduction to working with Next-Generation Sequencing (NGS) data. It targets individuals who have access to NGS data and want to learn how to work with this data and what the possibilities and limitations of NGS are. Lectures will be complemented with practical sessions in which the student will gain hands-on experience with various tools and techniques.
Subjects that will be covered include:
- NGS: an introduction to methodology and techniques;
- Basic statistics of NGS data, e.g. coverage;
- Aligning the sequence reads;
- Calling sequence and structural variants;
- Dealing with various file formats (samtools, VCFtools, GATK);
- Annotating sequence and structural variants;
- Evaluating functional effects of the genetic variants on proteins;
- Conversion to other formats;
- Single variant and Collapsed genotype analyses with various tools (e.g. seqMeta, RAREMETAL and RVtest);
- Finding variants with recessive effects and compound heterozygosity;
- Search for rare variants in families and population based studies for complex phenotypes;
- Search for rare variants in Mendelian disorders, and
- Imputation of sequence variants.

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07 Aug 2017 - 11 Aug 2017
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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07 Aug 2017 - 11 Aug 2017
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 will focus on modern ways to describe data such as tables, graphs, distributions and summary statistics (mean, standard deviation, median, quartiles), as required in the international scientific literature. The analysis of survival data will also be envisaged, in particular the renowned Kaplan-Meier survival curve. Finally, the association between variables will be discussed (correlation, relative risk, odds ratio and regression) as well as the agreement between observers (Cohen kappa coefficient).

The course will then turn on the relation between the population and the random sample and on how effects observed in the sample can be generalized to the total 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). 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 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 (and 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 international medical literature. The basic principles underlying non parametric tests will be outlined and the most used distribution-free tests mentioned (Spearman correlation, Wilcoxon signed rank test, Mann-Whitney U-test, Kruskal-Wallis and Friedman tests).

All topics covered in the course will be illustrated using real data from the medical and biomedical literature and applied during practical sessions.

Written exam on Friday 2 September 2016 (only for NIHES MSc students and for ‘keuzevak students’), date resit is to be announced. 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.

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

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07 Aug 2017 - 11 Aug 2017
Clinical Trials [ESP14]

About this course

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

This intermediate level course provides insights to the primary design, conduct and analysis issues that must be considered by the many disciplines that collaborate in the conduct of clinical trials.

We will consider 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 defintion of clinical outcomes and assumptions needed to define the trial size. Topics regarding the conduct and implementation of clinical trials will cover the need for trial registration, choice of randomization strategies, blinding, prevention and handling of missing data, monitoring of the study, the tasks of an independent data monitoring committee, 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.

Teaching methods:
Lectures and group works on critical appraisal of trial protocols and published trial results.

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07 Aug 2017 - 11 Aug 2017
Topics in Meta-analysis [ESP15]

About this course

Faculty: Prof. Matthias Egger, MD PhD & Prof. Olaf Dekkers, MD 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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07 Aug 2017 - 11 Aug 2017
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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07 Aug 2017 - 11 Aug 2017
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.

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07 Aug 2017 - 11 Aug 2017
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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07 Aug 2017 - 11 Aug 2017
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 Searching Genes for Complex Disorders, the course offers an excellent introduction to genetic epidemiologic research for 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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07 Aug 2017 - 11 Aug 2017
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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14 Aug 2017 - 18 Aug 2017
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.

Written exam on Friday 2 September 2016 (only for NIHES MSc students and for ‘keuzevak students’), date resit is to be announced. 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.

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

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14 Aug 2017 - 18 Aug 2017
Methods of Public Health Research [ESP11]

About this course

Faculty: Prof. Lex Burdorf, Ir. PhD

This course aims to provide an introduction to the 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. The course targets three key issues: (1) summary measures of population health, such as standardised morbidity rates and life expectancy, (2) measures of association and relative importance of specific causes for population health, and (3) evaluation of population interventions through community trials and alternative designs based on natural experiments. Designs and methods will be illustrated in lectures and exercises and application will be discussed in hot topics, such as health inequalities; causes and consequences of ageing; avoidable diseases such as cancer; and exposure assessment in environmental epidemiology.

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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14 Aug 2017 - 18 Aug 2017
Cohort Studies [ESP39]

About this course

Faculty: Prof. Javier Nieto, MD PhD MPH

This course will provide an introduction to the cohort and other longitudenal 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-cohort 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 in small group 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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14 Aug 2017 - 18 Aug 2017
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, 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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14 Aug 2017 - 18 Aug 2017
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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14 Aug 2017 - 18 Aug 2017
Causal Inference [ESP48]

About this course

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

The goal of many epidemiologic studies is to quantify the causal effect of an 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 (causal) methods can be used under less restrictive conditions than traditional statistical methods. For example, causal methods allow one to estimate the causal effect of a time-varying exposure in the presence of time-dependent confounders that lie on the causal pathway between exposure and outcome.

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.

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14 Aug 2017 - 18 Aug 2017
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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14 Aug 2017 - 18 Aug 2017
Genomics in Molecular Medicine [ESP57]

About this course

Faculty: Prof. André Uitterlinden, PhD, Joyce van Meurs, PhD, Fernando Rivadeneira Ramirez, 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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14 Aug 2017 - 17 Aug 2017
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 Master Classes pages, find these in the drop-down menu of Programme.

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

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14 Aug 2017 - 18 Aug 2017
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 and the Bayes factor. 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.

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14 Aug 2017 - 18 Aug 2017
Fundamentals of Medical Decision Making [ESP70]

About this course

Faculty: Prof. John Wong, MD PhD

Introduction to Methods for Decision-making in Health Care: Integrating evidence and values
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 physicians 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 modeling and cost-effectiveness analysis in order to integrate evidence and values for optimal care choices.

Teaching methods: Interactive lectures, exercises and practicums.

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14 Aug 2017 - 18 Aug 2017
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.

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21 Aug 2017 - 25 Aug 2017
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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21 Aug 2017 - 25 Aug 2017
Primary and Secondary Prevention Research [ESP45]

About this course

Faculty: Prof. Oscar Franco, MD PhD and Prof. Harry de Koning, 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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21 Aug 2017 - 25 Aug 2017
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.

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21 Aug 2017 - 25 Aug 2017
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).

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21 Aug 2017 - 24 Aug 2017
Erasmus Summer Lectures [ESP64]

About this course

In these series of lectures, timely topics in study design of epidemiologic and clinical studies will be addressed. Four renowned faculty members 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 Master Classes pages, find these 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 MC University Medical Center and public at large.

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21 Aug 2017 - 25 Aug 2017
The 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.

The course is particularly intended for students who have completed their data collection and move towards data analysis. No prior knowledge is required although understanding of basic epidemiology is helpful.

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21 Aug 2017 - 25 Aug 2017
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.

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21 Aug 2017 - 25 Aug 2017
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.

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21 Aug 2017 - 25 Aug 2017
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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21 Aug 2017 - 25 Aug 2017
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 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.





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Erasmus Winter Programme (EWP)

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

See overview of all available courses