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Regressions with R: an Overview

  • 9:30am to 1pm
  • 4 days

Overview

This short course will give you an overview of a variety of regression types and models using the R software, via libraries including lm, glm, and gamlss.

You'll learn about ways of performing model fitting, model diagnostics, predictions and relevant graphical displays

The regression types you'll cover include:

  • linear regression
  • logistic regression
  • ordinal logistic regression
  • Poisson regression
  • negative binomial regression
  • survival/cox-proportional hazards
  • multilevel linear regression

This course takes place online, over four mornings (9:30am to 1pm). 

This course is delivered by UCL's Centre for Applied Statistics Courses (CASC), part of the UCL Great Ormond Street Institute of Child Health (ICH).

Eligibility

You'll need to be able to use R to perform basic data manipulations and produce summary tables and graphs. (These skills are taught on our one-day Introduction to R course).

Additionally, you'll be expected to have a basic understanding of common statistical tests and concepts, such as p-values and confidence intervals, as these will not be taught during this workshop. (These are taught on our five-day course - Introduction to Statistics and Research Methods.)

Computers and software

You'll need to have R and Rstudio installed on your computer (installation guidelines will be made available two weeks before the course).

Learning outcomes

By the end of this course you should be able to:

  • understand how to use R to fit regression models
  • fully understand the use of the lm, glm, clm and survival R functions
  • correctly interpret the given output from the illustrated regressions
  • investigate how well a given model fits the data

Certificates

You can request a certificate of attendance for all of our courses once you've completed it. Please send your request to ich.statscou@ucl.ac.uk

Include the following in your email:

  • the name of the completed course for which you'd like a certificate
  • how you'd like your name presented on the certificate (if the name/format differs from the details you gave during registration)

Cost and concessions

The fees are:

  • External delegates (non UCL) - £350
  • UCL staff, students, alumni (including ICH/GOSH) - £175*

* valid UCL email address and/or UCL alumni number required upon registration

Cancellations

Read the cancellation policy for this course on the ICH website. Please send all cancellation requests to the course administrator

Find out about other CASC statistics courses

CASC's stats courses are for anyone requiring an understanding of research methodology and statistical analyses. The courses will allow non-statisticians to interpret published research and/or undertake their own research studies.

Find out more about the full range of statistics courses, and the continuing statistics training scheme (book six one-day courses and get a seventh free.)

Course team

Dr Eirini Koutoumanou - Course Lead

Dr Eirini Koutoumanou - Course Lead

Eirini has a BSc in Statistics from Athens University of Economics and Business and an MSc in Statistics from Lancaster University (funded by the Engineering and Physical Sciences Research Council). She joined UCL GOS Institute of Child Health in 2008 to develop a range of short courses for anyone interested in learning new statistical skills. Soon after, CASC was born. In 2014, she was promoted to Senior Teaching Fellow. In 2019, she successfully passed her PhD viva on the topic of Copula models and their application within paediatric data. Since early 2020 she’s been co-directing CASC with its founder, Professor Angie Wade.

Dr Dean Langan - Course Lead

Dr Dean Langan - Course Lead

Dean is a Senior Teaching Fellow in CASC. He has a Bachelor’s degree in Mathematics from University of Liverpool, a Master's degree in Medical Statistics from University of Leicester, and a PhD from University of York for his research in statistical methods for random-effects meta-analysis. He's worked as a statistician on a number of clinical trials related to stroke and myeloma at the Clinical Trials Research Unit in Leeds. His specialist areas include statistical methods for meta-analysis, R programming, clinical trial methodology and research design.

Course information last modified: 1 Nov 2021, 13:27