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Biostatistics courses

Keywords Statistics

The Biostatistics courses in R will be organized in June and November 2021. The course in the spring is already fully booked. You can apply for the fall 2021 or for 2022.

Courses outline

  1. WA Course - basic statistics- 2 day course : registration at WA or leerportaal - only for NKI and AVL employees. Send an email to secretariaat.wa@nki.nl for more information and registration.
  2. Introduction to R
  3. Medical Statistics in R

 Dates 2021:

  1. not known yet. you can contact the WA.
  2. June 7 - 11, 2021 and November 8-12, 2021 - Introduction to R (online - Live, not known yet)
  3. June 21-25, 2021 and November 22-26 - Medical Statistics in R (online  or Live, not known yet)
  4. next course dates not known yet. In AUMC-VUmc (advanced) -  fee 320 Euro.

Dates in 2021 : look at Schedule and Registration 

Location:

Netherlands Cancer Institute (NKI), Amsterdam 

Language: English

More Information

Outline
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Outline


Introduction to R


Any researcher is welcome to follow this course. No previous knowledge of R is required.

Medical Statistics in R


In this course an introduction to basic statistical methods useful for biomedical data analysis will be given. It is for any professional involved in research that requires using statistical methods.

During the course we will alternate between lectures and practicals, allowing for plenty of interaction and illustration with examples of practical interest.

We will use R (http://www.r-project.org) for all practicals. Participants with no experience in R are strongly advised to follow an introductory R course prior to following this course (see pre-requisites  for suggestions).

Link to pdf or book

What is R?

R is an open-source, free environment for statistical computing and graphics. It provides a large repository of statistical analysis methods, both classic and new. However, R has a steep learning curve, due partly to its using a command-line type of user interface, rather than the usual pull-down menus. This 3-day course aims at helping researchers climb this curve, enabling them to perform basic data analysis and graphic displays at the end of the course, as well as giving a platform from which they can deepen their R knowledge later on if necessary.

Goals & Topics

After the course you will be able to:

  • understand and write simple R programs
  • use R to perform basic statistical analyses of your own data tables
  • generate analysis reports from your own data in html or pdf formats, using RMarkdown

We will cover the following topics:

  • R expressions and formula objects
  • R data objects (vectors (arrays), data frames (tables), lists, matrices) creation and usage
  • R functions for descriptive statistics and linear model fitting
  • installing additional libraries
  • histograms, scatter plots, boxplots (in pure R )

Course lectures
Renee X. de Menezes
Renaud Tissier

 

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Course Organization and Material
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Course Organization and Material


The course will be given by alternating short lectures and practicals. This allows for plenty of opportunity for solidifying concepts in a concrete manner.

We will give solutions to all exercises via R scripts in RMarkdown files. These can be used as reference material by the students after completing the course, for example to run their own analyses.

All course material will be made available from this page.

References


Basic material will be provided during our lectures. The lectures largely coincide with the content of Peter Dalgaard's book:

https://www.springer.com/gp/book/9780387790534

which is also an excellent reference for basic R.

For a more advanced treatment that includes introductions to bootstrap, robust regression and clustering, as well as more advanced R functions, which will not be covered during this course, we refer interested students to Bill Venables and Brian Ripley's book:

https://www.springer.com/gp/book/9780387954578

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Pre-requisites
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Pre-requisites

 

The course requires elementary statistics knowledge, but assumes no prior programming knowledge.

Participants must bring their own laptops capable of running R and RStudio. Please install R (from the Comprehensive R Archive Network-CRAN, for example from this mirror) and download and install RStudio before the course. Optionally, you may additionally download and install a console version of R.

Participants are entitled to ECTs after following our courses, so long as they complete the final assignment. This is typically a RMarkdown report, completed by each participant.
No accreditation for Medical Doctors available.

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Schedule and Registration
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Schedule 2020 and 2021 - Registration


The schedule for 2021:

Introduction to R 
Monday-Friday June 7-11 - 9.00-16.30 hrs
Monday-Friday November 8-12 - 9.00 - 16.30 hrs

Medical Statistics in R 
Monday-Friday June 21-25 - 9.00-16.30 hrs
Monday-Friday November 22-26 - 9.00-16.30 hrs

For both courses, 30 people can join. 

You can register by filling in this form (use Edge, Firefox or Chrome). Please always register; even if you have done this before. This way we know you are interested in the R-courses.

For questions, mail Patty Lagerweij : p.lagerweij@nki.nl 

Fee                                                                                                        

The course is free of charge for employees of the NKI-AvL and for Ph.D. students of the OOA (Onderzoeksschool Oncologie Amsterdam).
For all others, the fee is :
Introduction to R (3 days) - 150 EUR academia / 300 EUR outside academia
Medical Statistics in R (5 days) - 250 EUR academia / 500 EUR outside academia

  • Registration Form
Faculty
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Group Menezes

Use this link to see information about Rene Menezes on the NKI website.

 

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