This course provides a theoretical overview and detailed practical knowledge concerning statistical analyses of social psychological data.
Aim and content: The course will explain statistical techniques for the evaluation of biomedical data. It provides an introduction into design aspects, methods of summarizing and presenting data, estimation, confidence intervals and hypothesis testing, including multivariable regression methods for the assessment of association. Although the course focusses somewhat on methods and examples from clinical research, it should be useful for experimental researchers as well. The emphasis will be on practical application and interpretation rather than theory.
An optional half-day introduction to the statistical software SPSS will be given for those not familiar with this program.
In line with national agreements, clinical researchers are required to follow the "Basic regulation and organization of clinical research" (eBROK; www.NFUbrokacademie.nl ) course to obtain the corresponding certificate
For practical information (such as dates on which the course takes place and registration), you can contact visit the page mentioned above or contact us via email info@NFUbrokacademie.nl .
Credits: 1,5 EC
The aim of the course is to provide better knowledge and understanding of the development of prediction models that are relevant to real-life practice. We will focus on the various methods for selecting variables, and the pros and cons of these different methods. Once the prediction model has been developed, it is important to assess the quality of the prediction model. For example, we will look at whether the predictions of the model are accurate and during the course, we will also consider the various ways of measuring accuracy.
Short description: The course involves insight into the procedural side of datamanagement support (what do PhD students have to do themselves and for which questions and appeal can be made on the datamanagement department of the APH institute). The focus of the course will also be on the substansive aspects of datamanagement before and during data collection. After this course participants know where to go for support, what is expected of them and how to use the information and guidelines on the website of the datamanagement department.
This course is designed for scientific personel that is involved in clinical research but does not initiate clinical research themselves. The course covers national rules and regulations regarding research on human subjects and good clinical practice. The good clinical practice course consits of half a day education and will be closed of with a digital examn that will take another half day. Those who pass will recieve a certificate.
The course is focused on the respectful and responsible use of laboratory animals in biomedical research.
In deze drie daagse cursus over mediatie analyse wordt aandacht besteedt aan de theoretische achtergrond van mediatie analyse, de analyse van verschillende soorten mediatie modellen en de interpretatie van de resultaten van mediatie analyse. De cursus bestaat uit hoorcolleges en computerpractica.
The course is designed for PhD-students, practitioners and applied researchers working in the field of epidemiology, medicine, public health, psychology, human movement sciences. The course is designed for everybody who wants to learn about missing data because missing data may be present in your own research and you are going to start with your data analysis or you want to learn how to judge other articles or research grants who report missing data. It is also important to be able to judge the impact of missing data for practice-related research.
This four-day course will explain the basic concepts of mixed models. It is an applied course, so the emphasis lies on the interpretation of the results from the mixed model analyses and not on the mathematical background. The course centres on the two most important applications of mixed models - multilevel analysis and longitudinal data analysis. Lectures are given in the morning and in the afternoon a computer practical is given using the statistical programs STATA and SPSS.
Het zelf uitvoeren van (klinisch) epidemiologisch onderzoek, maar ook het beoordelen van de resultaten van anderen, vereist grondige kennis van de beginselen van epidemiologische data-analyse. Hierbij speelt de biostatistiek een belangrijke rol. Met behulp van methoden en technieken van de biostatistiek kunnen de uitkomsten van epidemiologische onderzoeken worden samengevat (beschrijvende statistiek) en verder worden geïnterpreteerd en gekwantificeerd (inferentiële statistiek). Daarbij heeft men te maken met begrippen als kansverdelingen, precisie, puntschatting, betrouwbaarheidsinterval, hypothese, p-waarde, etc.
You will learn how to design psychological experiments and how to implement these using the OpenSesame software package and the Python programming language.
De belangrijkste eenvoudige statistische technieken worden kort besproken en vervolgens worden deze uitgebreid met o.a. regressietechnieken. Er wordt veel aandacht besteed aan de keuze van de juiste techniek, de interpretatie van de resultaten en de samenhang tussen eenvoudige technieken en de regressietechnieken.
De snelle groei van het aantal systematische reviews (inclusief meta-analyses) dat in toonaangevende tijdschriften en boeken wordt gepubliceerd, toont het belang aan van actuele kennis over het uitvoeren en interpreteren van deze vorm van literatuuronderzoek. Gegevens uit systematische reviews worden gebruikt bij de onderbouwing van behandelprotocollen of -richtlijnen, bij het nemen van beleidsbeslissingen, bij het beoordelen van subsidieverzoeken en in de voorbereiding van eigen onderzoek. De cursus is onder meer geschikt voor (para-)medisch onderzoekers die ter voorbereiding of als onderdeel van eigen onderzoek een systematische review willen uitvoeren en rapporteren
Working with radioactivity requires special training. Such a training is offered at the Radionuclide Center on a regular basis. The training is at the 5B level and is acknowledged by the national government. Two times a year the Radionuclide course students can participate in the national exam level 5B. The course takes one workweek and is meant as a basic training. It is about 60% theory and 40% practical training. The selection of the experiments is based on the teaching of basic techniques, the introduction and handling of a variety of detection devices and on the learning of how to interprete the data obtained.
Aim and contents: The aim of CaRe is to foster the education of highly qualified, independent and scientific researchers, with an open mind for collaborative research in primary care, transmural care, public and occupational health and health policy. The PhD educational programme includes courses on epidemiology, health, and healthcare
The University Library provides training on Research Data Management (RDM) for PhD students. Good RDM (e.g. storing, sharing, archiving, describing your research data) contributes to research transparency and integrity. Due to the advance of new technologies, data volumes and numbers of files are constantly increasing. For that reason good data management is an essential part of data-driven research as well.
In this workshop, we will introduce and discuss the different aspects of RDM which typically need to be covered in a data management plan (DMP). At the moment, this training concerns a Research DMP, as opposed to a Clinical DMP (due to developments in Amsterdam UMC and the RDM support desk that is being set up in this context, the two types of DMPs will be integrated in the future). Typically, a Research DMP covers topics like data description, data storage during research, sharing data with colleagues, data archiving after research and data citation. The various components of RDM will be related to the FAIR principles (that is, principles to make data Findable, Accessible, Interoperable and Reusable). We will also address the ethical and legal framework, including the General Data Protection Regulation (the new EU-law on privacy which came into effect in May 2018).
In this training, you'll learn why good RDM is necessary and how it can be beneficial to your research. In an interactive workshop, we will provide you with practical guidelines and instruments to manage your data properly. You will be working on a DMP for your own research, so that you can apply the things you learn to your own project. In the near future, all researchers at VUmc will have to write a DMP. In other words, not only studies financed by an external funder or falling under the scope of the Medical Research Involving Human Subjects Act (WMO) have to deliver a DMP, but all types of research will have to. This course can be a good opportunity to fulfil this requirement
This course will be taught in two different versions: one for clinical research and one for preclinical studies. Please check out the course dates to see which one applies to your research and sign up for the relevant version.
This training requires some preparation from your side. You will be asked to study some information about RDM (a few short articles and a website). In addition, you need to write a first draft of a research DMP, which will be worked out in more detail during the workshop. Estimated time investment for the preparation: 20 hours.
Detailed overview of time investment :