Course

Introduction to R

R (https://www.r-project.org/) is a programming language and software environment for carrying out computations, manipulating and analyzing data, and creating various types of plots and graphics. R has become the 'lingua franca of statistics' and the software of choice for analyzing data in various disciplines.

Moreover, R is free, open-source, and runs on various platforms (Windows, MacOS, Linux, etc.). However, for many researchers, getting up and running with R remains a hurdle due to the command-driven nature of the software. The purpose of this course is to lay the necessary foundation for becoming a proficient R user.

Prerequisits

Familiarity with basic statistical concepts and methods as used in the health, social, and natural sciences is helpful when following the course.

Course participants should bring a laptop with the current version of R installed (which can be downloaded from https://cran.r-project.org/). Also, while not necessary, installing RStudio (an integrated development environment for R) is highly recommended (which can be downloaded from https://www.rstudio.com/products/rstudio/download/).

Dr. Wolfgang Viechtbauer
Department of Psychiatry and Neuropsychology
Phone: +31 (43) 388-4170
E-mail: wolfgang.viechtbauer[at]maastrichtuniversity[dot]nl
Website: http://www.wvbauer.com

Contents

  • history of R
  • basic data structures
  • data import/export
  • data inspection
  • data manipulation
  • graphing data
  • t-tests and analysis of (co)variance (*)
  • linear regression (*)
  • analyzing categorical data / logistic regression (*)
  • survival analysis and Cox models (*)
  • mixed-effects models (*)
  • add-on packages
  • basic programming structures
  • writing functions
  • writing documents with Rmarkdown

(*) Emphasis here is more on the general syntax as used in R and less on the statistical details of the various procedures.

Duration
Three full days (starting at 9:00 and ending around 17:00, with a lunch break around 12:00 and coffee/tea breaks as needed).

Method
Interactive hands-on lectures.

Literature
There are no required readings but the following book is a popular reference:
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage.

Application

PhD Secretary
Phone: +31 (43) 388-5613
Available: Mondays, Tuesdays, and Thursdays from 8:30 to 12:00
E-mail: aioonderwijs[at]maastrichtuniversity[dot]nl
Maximum number of participants: 25
* Please note: when you subscribe, you will receive a response from the aioonderwijs emailbox after 17 September 2019.

Course fees

PhD candidates (Promovendi) of FHML, MaCSBIO, M4I and MERLN: no fee
Master students: no fee (*)
Other: €500,00
(*) PhD candidates and other participants are given preference. If some spots are still available, then Master students can apply.

Coursedates

October 23 and 25: N4.22, UNS 60
October 24: Co Greep meeting room (M 5.01, UNS 60)
All course days are from 9.00-17.00. You need to bring a (fully charged!) laptop.