INTERFACULTY CENTER DATA PROCESSING AND STATISTICS

HUMAN SCIENCES - LIFE SCIENCES & MEDICINE
Interfaculty Center Data processing & Statistics

methodological and statistical support to help make a difference

ICDS provides complementary support in methodology and statistics to our research community, for both individual researchers and research groups, in order to get the best out of them. ICDS aims to further enhance the quality of both the research and how it is communicated.

At Your Service

for our VUB-UZ Brussel research community

request

Terms of Service - Ethical Code

Coordinator

Prof. Dr. Kurt Barbé

Statistical Consultants

Dr. Wilfried Cools (Jette)
Dr. Oscar Olarte (Jette)
Dr. Lara Stas (Etterbeek)

Supporting Researchers (BISI)

Prof. Dr. Kurt Barbé
Prof. Dr. Ronald Buyl
Dr. Iris Steenhout
Dr. Oscar Olarte
Drs. Susanne Blotwijk
Drs. Sven Van Laere
Drs. Hanif Shaikh
Drs. Camille Raets

Financially supported by

Research board, University Medical Campus

umclogo
Vice-rectorat Research Policy

 

Whom We Serve

Master Student (Thesis) in Jette
to get a push in the right direction

General guidance on strategies, techniques, software and communication of design and statistics.

Researcher
to get your study and analysis up and running

A look over your shoulders to ensure appropriate methodology and statistics and help its communication, possibly taking over parts of the data analysis.

Research Groups
to get fully dedicated support for your study

Full involvement in study design and/or data analysis, in optimizing the data collection and processing for recurrent studies and in bringing in the latest statistical techniques.

Committees
to help safeguard research quality and ethics

Reviewing and refereeing research protocols and proposals to promote efficient / effective studies, reducing costs for patient, lab animal, researcher.

How We Serve

Consultancy
asking the right questions the right way

Statistical and methodological advice on data analysis and data collection (eg., sample size), on communicating statistics and results, on writing protocols and research proposals.

Data Analysis
getting the relevant information out of it

A full collaboration implies taking our responsability for implementing (parts) of the analysis, communicating the results and responding to remarks made by reviewers.

Tutoring
learning to do things yourself

Workshops and seminars are provided to enhance the existing proficiency in statistical and methodological reasoning where needed.

Automation
getting the computer to do it for you

Parts of the data collection, data analysis and reporting can be automated to avoid repetitive work, errors and time loss, and to promote uniformity.

Resources

Workshops

Sample Size Calculation with GPower
Workshop to introduce he necessary concepts, covering power, effect size and type I/II errors, with small illustrative exercises to touch on relevant statistical reasoning. While focusing mainly on the comparison of 2 independent groups, several extensions are highlighted. Get online slides or pdf download.

 

Presentations

Methodological & Statistical issues in research proposals
Info session for experienced researchers to highlight the research aim and design as part of a research proposal, touching on types of research aims (confirmatory, exploratory, preparatory, techn(olog)ical) and different aspects of research design (quantity & quality of observation and generalization). Get webpage, for online slides or pdf download.

 

Shiny Apps

All Shiny Apps deployed at icds.shinyapps.io
The Apps can be run locally too, using the R package `shiny` with the function
runGitHub('name_of_shiny_app','ICDS-VubUZ')

alpha spending (sample size calculation)
sample size calculation with Alpha Spending, using simulation
runGitHub('simAlphaSpending','ICDS-VubUZ')

effect sizes (two way anova and repeated measures)
effect size calculation based on group means and pooled standard deviation
runGitHub('effectSizes','ICDS-VubUZ')

sample sizes for T-test (didactical tool)
explore relation data and independent t-test
runGitHub('shinyT','ICDS-VubUZ')