Courses

NIHES offers various short courses in specific areas of clinical and public health research open to everyone interested with a good working knowledge of the English language.

For participants of participating institutes and partner institutes of NIHES we offer reduction on our fees for short courses. Please check the detailed information of your course of interest for more information.

Our short courses are accredited by the Netherlands-Flemish Accreditation Organisation (NVAO) as part of our Master of Science programmes. For more information, go to http://www.nvao.net.

Courses programme overview

29 Aug 2016 - 16 Sept 2016
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

19 Sept 2016 - 14 Oct 2016
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

17 Oct 2016 - 11 Nov 2016
Clinical Epidemiology [CE02]

About this course

In clinical epidemiology, research is focused on questions of diagnosis, prognosis and etiology. To address these questions, several research options are available, including intervention trials and case-control studies using data obtained in a clinical setting. In addition, combined with decision analysis, results from clinical epidemiologic research may be used in treatment decision.

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

17 Oct 2016 - 21 Oct 2016
Public Health Research: Analysis of Population Health [HS02a]

About this course

Public Health Research: 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

24 Oct 2016 - 28 Oct 2016
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

31 Oct 2016 - 04 Nov 2016
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

14 Nov 2016 - 18 Nov 2016
Methodologic Topics in Epidemiologic Research [EP02]

About this course

This course elaborates upon major concepts in epidemiologic research with a short review on their historic development. The course will begin with addressing the development of epidemiologic thinking about causation and causal inference in epidemiologic studies. The course further focuses on methods to investigate confounding and effect-modification. Finally, it will address the consequences of misclassification bias in epidemiologic studies. The course is based on short lectures followed by small group and plenary discussions where participants are actively involved in discussing major papers in the field as well as exercises with their peers.

Read More

14 Nov 2016 - 18 Nov 2016
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

21 Nov 2016 - 09 Dec 2016
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 8 and 9, 2016

Read More

Next course is in May, 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.

Read More

Next course is in January, 2017
Medical Demography [HS04]

About this course

The first day of the course starts with an overview of the different types of \"what if\" questions raised in public health, and an overview of the types of models that could be used to address such questions. Next we will briefly discuss population projection techniques. Further, the student will learn to apply the life table, which is a simple yet powerful technique to model the population dynamics underlying public health.

The second day will focus on summary measures that combine mortality and morbidity estimates, such as healthy life expectancies and disability-adjusted life expectancy. It will discuss two types of life tables that are used to this end: the Sullivan life tables, and the multi-state life tables. Attention is also given to assessing the effect on population health of specific diseases, such as stroke or cancer.

The third day will discuss the use of risk factor models, which are applied to assess the ways in which changes in risk factors such as smoking and overweight could affect population health. Examples will be based on the Dynamo model, which is a new, comprehensive model to be used in health impact assessments across Europe.

The last day will illustrate the use of population health models in a series of studies that evaluated the population health impact of different types of interventions. The emphasis is given to the Prevent model, which will be applied to assess the impact of life style changes on future cancer incidence.

The course consists of lectures and many computer exercises.

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

Read More

Next course is in April, 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.

Read More

Next course is in April, 2017
Scientific Speedreading [SC18]

About this course

You are probably familiar with speedreading, but participating in a workshop is something you wouldn’t do that quickly. Increasing your reading speed twofold without it affecting comprehension just seems too good to be true. You could easily use the time of learning how to read faster for things like studying.

In 2011, this same skepticism led us to investigate the theory behind speedreading from a scientific perspective. In collaboration with the Neuroscience department of the Erasmus Medical Center, numerous techniques were tested for their ability to improve reading speed and comprehension. This knowledge was applied in a series of courses that were featured in the Quest magazine.

Starting October 2014, NIHES is offering a renewed version of this course that includes the use of non-invasive eye-tracking technology. During this 3.5-hour workshop, you will be doing hands-on experiments to understand the theoretical background of speedreading. The newly learned techniques will then be applied to reading material, which we will try to provide in your native language. Additionally, you will receive a two-month subscription to our online course environment with exercises to further improve your reading speed (3 hours per week). Furthermore, exams will be performed within this environment to test your progress. Successful participation will result in receiving a certificate that proves you attended this course. Credits do not count toward the NIHES MSc or DSc programme.

Please apply via http://goo.gl/hXuh1P
For questions use the above form or email to speedreading@erasmusmc.nl

Read More

Next course is in March, 2017
Regression Analysis for Clinicians [EWP23]

About this course

This intermediate level course introduces the fundamental concepts of regression analysis. A unified approach to regression is taken, which emphasizes the common features of regression for quantitative and discrete response variables.

The course emphasizes the proper formulation and interpretation of regression models and uses several data examples from various health science fields to illustrate the concepts. Specific types of models illustrated by example will include linear regression, logistic regression, relative risk regression, and Poisson regression.

The course also emphasizes the assumptions of regression analysis and the impact of violations of the assumptions on inference. As one example of this, robust variance estimates will be presented as one method for accommodating departures from assumptions about response variance, such as the constant variance assumption of linear regression. A brief introduction to specialized topics, including regression analysis of longitudinal and multi-level data, will also be given.

Teaching methods
The mornings will consist of lectures in which the fundamental concepts are presented and illustrated through applications to real and simulated data sets. The mathematical content is limited to the minimum required for an understanding of the concepts. The afternoon computer lab sessions provide an interactive forum for discussion of the concepts presented in the morning and their application to real data sets using SPSS statistical software.

This course is equivalent to the Erasmus Summer Programme course Regression Analysis (ESP09) in August.

Read More

Next course is in April, 2016
Nutrition & Physical Activity [EXC02]

About this course

The primary aim of the nutrition and physical activity module is to describe the measurement and epidemiology of nutrition and physical activity.
The module will cover definitions, methods to assess nutrition and free-living physical activity, epidemiology of nutrition in relation to cancer, aspects of cardiovascular disease and malnourished populations, physical activity and physical activity recommendations for public health. Methods to assess nutrition include questionnaires, biomarkers and food records and those for physical activity include self-reported methods and objective measurements techniques. The amount of physical activity necessary for different health outcomes, such as CVD, obesity and diabetes will be discussed and recent activity recommendations for different age groups will be considered.
Debates by students on topics covered by the module will be included.

Read More

Next course is in September, 2016
Principles of Identifying and Recognizing Adverse Events and Safety Signals [D4M1]

About this course

For up-to-date course information please check:
http://www.eu2p.org/course-catalogue/medicines-risk-identification-and-quantification/principles-of-identifyingand-recognizing-adverse-events-and-safety-signals

Read More

Next course is in September, 2016
Introduction to Benefit-Risk Assessment and Pharmacoeconomics in Decision Making [D5M1]

About this course

For up-to-date course information please check:
http://www.eu2p.org/course-catalogue/medicines-benefit-risk-assessment/introduction-to-benefit-riskassessment-and-pharmacoeconomics-communication-in-decision-making

Read More

Next course is in October, 2016
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

Next course is in October, 2016
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

Next course is in November, 2016
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 check:
https://www.molmed.nl/

Read More

Next course is in January, 2016
Substantiation and Quantification of Risks [D4M2]

About this course

For up-to-date course information please check:
http://www.eu2p.org/course-catalogue/medicines-risk-identification-and-quantification/substantiation-andquantification-of-risks

Read More

Next course is in January, 2016
Environmental Epidemiology [EXC05]

About this course

This intensive 3,5 day module focuses on methodologies in environmental epidemiology with examples from current topics such as air pollution, exposure assessment, cluster analysis, risk assessment using occupational epidemiology, consequences of climate change on health, uses and misuses of GIS, conflicts and disasters. Most public health epidemiology courses neglect or gloss over environmental hazards, including the role of occupational epidemiology, and this module is designed to redress the balance.

Read More

Next course is in January, 2016
Women's Health [EP19]

About this course

The department of Epidemiology, in collaboration with the department of Internal Medicine at Erasmus University Medical Center, offers medical and health professionals a comprehensive course in Women's Health. This course brings together experts in women's health from a multitude of disciplines and provides participants with resources that will assist them in broadening and strengthening clinical care and research programs that are aimed at improving women's health and well-being. The course will focus on the critical issues that affect women's health throughout the life cycle.

Our main purpose is to provide participants interested in improving women’s health and well-being with essential knowledge and principle skills from several disciplines.

For NIHES Master students, this is a 3-day elective course. For people who attend this course as a short course, it is also possible to attend 1, 2 or 3 days of this course, as part a, b and c. Topics for each course day is to be announced:

Women’s Health: day 1 (EP19a)
Women’s Health: day 2 (EP19b)
Women’s Health: day 3 (EP19c)

The number of ECTS per day is 0.3 ECTS and the course fee per day is €210.00.

Information on last years course: www.nihes.nl/womens-health

Read More

Next course is in February, 2016
Advances in Genome-Wide Association Studies [GE03]

About this course

This 5-day advanced course aims to give an overview of new developments in the field of genome wide association studies for those with a background in genetics, epidemiology or statistics. In the first part of the course, issues concerning the design and analysis of genome-wide association (GWA) analysis will be covered using standard software such as Plink and genABEL. This part will include quality control, hands-on GWA analysis of quantitative and binary traits, methods to detect and correct for stratification, and to model epistastasis. In the second part we will extend to an integrated approach of data analysis including eSNPs and new developments in the analysis of whole sequence data.

Finally, we will discuss the perspectives for genetic testing in clinical practice. A major part of the teaching programme consists of hands-on exercises.

Read More

Next course is in February, 2016
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

Next course is in February, 2016
Health Services: Research and Practice [HS15]

About this course

The course explores the various hurdles in linking the principles of health services research with the realities of practice. Researchers will be taught how to become more sensitive to the information needs of practitioners, managers and policy makers and how to make their studies more practice-oriented while balancing methodological requirements.

The various steps of the research cycle will be discussed (formulation of the research question, study design, data-collection, analysis and presentation of results), and for each step the focus will be on the research-practice interface. In addition to classical research plans, the activities before the study is designed and the follow-up activities to promote implementation in practice, will be highlighted. Special emphasis will be put on the independent role of the researcher in the various forms of evaluation research. The course will be a combination of lectures and exercises and on the third day participants will be asked to present their own practice-based health services research proposal.

This module is offered in cooperation with the CaRe research school and is developed at the request of ZonMw (Netherlands Organisation for Health Research).

Read More

Next course is in April, 2016
Pharmacopsychology [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

Next course is in February, 2016
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.

Read More

Next course is in February, 2016
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

Next course is in February, 2016
Diagnostic Research [EWP05]

About this course

In this course we will discuss the principles of interpreting diagnostic test results and evaluating diagnostic tests.
We will first review basic concepts such as sensitivity, specificity, predictive probabilities, likelihood ratios, Bayes theorem and ROC curves. Then we will discuss possible forms of bias that can influence studies evaluating diagnostic test performance and a method to correct for verification bias. Diagnostic meta-analysis and summary ROC curves will be discussed.

Next we will focus on modeling issues in using decision analysis to model diagnostic decisions. Conditional independence and multivariable prediction rules will be explained. The week will end with determining the optimal operating point on the ROC curve and estimating target values for new diagnostic technology.

To get credit for the course you will need to perform assignments. We will do the assignments in part during class so bring a laptop. Expect to spend at least 2 hours per day finishing the assignments after class.

Please note that this course covers the same content on diagnostic research presented in NIHES course CE02.

Teaching Methods
Interactive lectures. Assignments performed in class and after class.

Read More

Next course is in February, 2016
Biostatistics for Clinicians [EWP22]

About this course

This course aims at introducing the basics of biostatistics, form an applied bio-medical perspective. Starting from some data sets collected to answer specific research questions, the objectives of statistical inference will be illustrated. These examples will also serve as key examples throughout the course.

Further, concepts such as population, random sample, randomization, and causality will be briefly discussed. Next, descriptive tools such as tables, graphs and summary statistics will be introduced. A lot of emphasis will be put on the relation between the population and the sample, and on how observed effects in the sample can be generalized to the total population.

After having discussed the concept of sampling distributions, confidence intervals and hypothesis testing will be introduced from an intuitive perspective. Afterwards, some frequently used testing procedures (unpaired and paired t-tests, chi-squared and Fisher exact tests, McNemar test) will be presented.

Specific topics will be discussed, including power and sample size analysis, equivalence testing, multiple testing, one-sided versus two-sided tests, significance versus relevance, measures for association (correlation, relative risk, odds ratio) , and aspects of non-parametric statistics.

Finally, the analysis of survival data will be discussed, including the complication of censoring, Kaplan-Meier estimation, and logrank and wilcoxon tests. All topics covered in the course will be illustrated using real data, and a lot of attention will be given to the use and misuse of statistics in the bio-medical literature. Emphasis is on correct interpretation of statistical results, rather than on mathematical detail.

Teaching methods
All tools will be introduced in a non-mathematical way. Instead, it is aimed to give intuition behind practical statistics and techniques. Theory will be illustrated extensively using examples from biomedical literature, with some discussion of what was done correctly and what is open for improvement.

This course is equivalent to Introduction to Data-analysis (ESP03).

Read More

Next course is in March, 2016
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.

Read More

Next course is in March, 2016
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. EWP24 also repeats the survival analysis of Biostatistical Methods II: classical regression models (EP03). In EPW24 more emphasis is put on the following topics (in comparison to EP03):
- Poison regression and Cox regression;
- Study design of survival studies, sample size en interim analysis.

Read More

Next course is in March, 2016
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

Next course is in February, 2016
Chronic Disease [EXC08]

About this course

The theme of the module is cardiovascular disease: from aetiology to public health. It is assumed that participants will have basic understanding of general epidemiologic principles before starting on this module. The emphasis will be on learning to recognise and evaluate the epidemiologic basis for policy and practice in cardiovascular disease prevention.

In the time available, it will obviously not be possible to cover comprehensively the topics listed, but simply to provide an introduction to the main issues in CVD epidemiology.

Proposed general areas to be covered:
International, national and secular trends;
Risk factors including diet;
Epidemiologic including intervention studies;
Current controversies and new ideas;
Strategies for prevention and public health policy.

Read More

Next course is in March, 2016
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.

Read More

Next course is in March, 2016
Advanced Clinical Trials [EWP10]

About this course

The Randomised Clinical Trial (RCT) is generally accepted as the most reliable way of assessing the efficacy of therapy. Reports on the results of RCTs appear in almost every issue of major medical journals. Medical doctors and other health professionals are expected to be able to judge the scientific merits and clinical relevance of published RCTs, even if they never actively participate in the design and/or execution of an RCT.
In recent years, the quality of trial reporting has improved. Influenced by the CONSORT statements, a certain uniformity in trial reporting both within and between journals has been achieved. Nonetheless, appraising trial reports remains a challenge and requires that several very different issues be addressed, such as
- Is the design of the trial described in the report concerned appropriate, given its stated objective? Is the trial large enough to potentially answer the question posed
- Both randomisation and (if applicable) double-blinding are procedural concepts. The correctness of the procedures involved cannot be verified from the data. This being so, does it look from what is stated in the methods section of the report concerned that the trial was indeed randomized and double-blind?
- Given acceptable procedures overall, is the data display informative and are the statistical methods used appropriate? Was the trial stopped earlier than planned, and if yes, what are the consequences? Is there data that one would like to know but that is not given, and if so, can this be derived from the data published?
- And finally, does the trial contribute to the resolution of a clinical problem that can be delineated in medical practice?

Teaching methods: Interactive lectures, reading published papers in class and as homework, in- class exercises using a laptop with Excel (Windows Office) or Numbers (Apple). Bringing your own laptop while attending classes is highly recommended.

Read More

Next course is in October, 2016
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.

Read More

Next course is in March, 2016
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

Next course is in March, 2016
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.

Read More

Next course is in March, 2016
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

Next course is in April, 2016
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

Next course is in April, 2016
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

Next course is in May, 2016
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

Next course is in , 2016
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

Read More

Next course is in January, 2016
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.

Read More

Next course is in April, 2016
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

Next course is in April, 2016
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

Next course is in May, 2016
Public Health in Low and Middle Income Countries [PU06]

About this course

This module aims to teach methods to assess the health of populations in low and middel income countries and to quantitatively evaluate the effects of interventions on population health. Students are taught use modern techniques as health impact assessment to predict changes in population health due to particular programmes, for example control programmes for infectious diseases.

Read More

Next course is in May, 2016
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.

Read More

Next course is in April, 2016
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.

Read More

Next course is in June, 2016
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'.

Read More

Next course is in June, 2016
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.

Read More

Next course is in June, 2016
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

Next course is in June, 2016
Advanced Psychology in Medicine [MP02]

About this course

Read More

Next course is in June, 2016
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

Next course is in June, 2016
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.

Read More

Next course is in August, 2016
Principles of Research in Medicine and Epidemiology [ESP01]

About this course

Faculty: Prof. Albert Hofman

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

Next course is in August, 2016
Introduction to Data-analysis [ESP03]

About this course

Faculty: Prof. Adelin Albert

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).

Read More

Next course is in August, 2016
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.

Read More

Next course is in August, 2016
Topics in Meta-analysis [ESP15]

About this course

Faculty: Matthias Egger & Olaf Dekkers

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

Next course is in August, 2016
Pharmaco-epidemiology [ESP21]

About this course

Faculty: Prof. Bruno Stricker

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

Next course is in August, 2016
Conceptual Foundation of Epidemiologic Study Design [ESP38]

About this course

Faculty: 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

Next course is in August, 2016
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

Next course is in August, 2016
Principles of Genetic Epidemiology [ESP43]

About this course

Faculty: Prof. Cornelia van Duijn

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.

Read More

Next course is in August, 2016
History of Epidemiologic Ideas [ESP53]

About this course

Faculty: Prof. Alfredo Morabia

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

Next course is in August, 2016
Masterclass: Advances in Epidemiologic Analysis [ESP64]

About this course

In this Master Class 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. Oscar Franco, MD PhD

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.

Read More

Next course is in August, 2016
Logistic Regression [ESP66]

About this course

Faculty: Stanley Lemeshow

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

Next course is in August, 2016
English Language [SC01]

About this course

All international Master of Science students, whose native language is not English, are required to attend the two proficiency tests of English Language (SC01). Your level of English will then be determined and, if proven necessary, you will be registered for the entire course.

This course is given at the beginning of the study year in order to enhance your learning experience during the programme.

Read More

Next course is in August, 2016
Regression Analysis [ESP09]

About this course

Faculty: Brian Marx

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).

Read More

Next course is in August, 2016
Methods of Clinical Research [ESP10]

About this course

Faculty: Prof. Henning Tiemeier

This course will give an introduction to clinical epidemiology. Due to its focus on the appropriate research design, measurement and evaluation, clinical epidemiology provides the scientific basis for the practice of medicine. The topics that will be covered in this course include risk (determinants of disease, pathogenesis), diagnosis (evaluation of diagnostic tests), prognosis (prediction of disease outcome), and management of disease (evaluation of therapy efficacy and safety). The course takes both a theoretical and a problem-oriented approach.

The teaching will be very interactive. Selected epidemiological concept and common problems such as multiple testing, variable selection and imputation are discussed in depth.

Read More

Next course is in August, 2016
Methods of Public Health Research [ESP11]

About this course

Faculty: Prof. Lex Burdorf

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.

Read More

Next course is in August, 2016
Survival Analysis [ESP28]

About this course

Faculty: Hein Putter

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.

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 Survival Analysis for Clinicians (EWP24).

Read More

Next course is in August, 2016
Cohort Studies [ESP39]

About this course

Faculty: Prof. Jonathan Samet, M.D., M.S.

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.

Read More

Next course is in August, 2016
Case-control Studies [ESP40]

About this course

Faculty: Prof. Moyses Szklo

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.

Read More

Next course is in August, 2016
Methods of Health Services Research [ESP42]

About this course

Faculty: Niek Klazinga

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

Next course is in August, 2016
Causal Inference [ESP48]

About this course

Faculty: Miguel Hernán

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.

Read More

Next course is in August, 2016
Genomics in Molecular Medicine [ESP57]

About this course

Faculty: André Uitterlinden, Joyce van Meurs and Fernando Rivadeneira

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

Next course is in August, 2016
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.

Read More

Next course is in August, 2016
Introduction to Bayesian Methods in Clinical Research [ESP68]

About this course

Faculty: Emmanuel Lesaffre

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.

Read More

Next course is in August, 2016
Fundamentals of Medical Decision Making [ESP70]

About this course

Faculty: Prof. John Wong

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.

Read More

Next course is in August, 2016
Joint Models for Longitudinal and Survival Data [ESP72]

About this course

Faculty: Dimitris Rizopoulos

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

Next course is in August, 2016
Health Economics [ESP25]

About this course

Faculty: Ken Redekop

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

Next course is in August, 2016
Primary and Secondary Prevention Research [ESP45]

About this course

Faculty: Oscar Franco and Harry de Koning

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

Next course is in August, 2016
Social Epidemiology [ESP61]

About this course

Faculty: Frank van Lenthe & Johan Mackenbach

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

Next course is in August, 2016
Markers and Prediction Research [ESP62]

About this course

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

Next course is in August, 2016
The Practice of Epidemiologic Analysis [ESP65]

About this course

Faculty: Arfan Ikram & Meike Vernooij

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.

Read More

Next course is in August, 2016
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

Next course is in August, 2016
Workshop Advanced Medical Writing and Editing [ESP71]

About this course

Faculty: Prof. Philip Greenland, MD

This is a hands-on course designed to improve medical writing skills for those who already have some experience in medical writing, including those with moderately extensive experience. Background requirements for the course include basic epidemiology and biostatistics as well as the optional ESP course \"The why and how of readable articles.\" In the absence of the latter short-course, students with experience in medical writing should also be able to participate actively.

In the first of the 5 three-hour class sessions, we will extensively review several published articles as a background for improving one’s own recognition of common writing mistakes. In the remaining sessions, we will cover the following topics:
1) Improving titles and abstracts;
2) Preparing an outline before writing a paper – why this is a good idea and how to do it;
3) Discussions of papers in progress by members of the class;
4) 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, to do at least one hour of reading and 1-2 hours of writing each day before class, and to submit a paper for review before the class begins on August 22.

Teaching methods
This is a hands-on workshop course. 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 passive learning from lecture.

Read More

Next course is in August, 2016
Genome-wide association studies [ESP74]

About this course

Faculty: Prof. Cornelia van Duijn, PhD and 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

Next course is in August, 2016
Epigenetics [ESP75]

About this course

Faculty: Jordana Bell, PhD

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