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This two-day 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 is delivered by UCL's Centre for Applied Statistics Courses (CASC) - part of the UCL Great Ormond Street Institute of Child Health (ICH).
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.)
Teaching and assessment
Teaching is from 10am to 3pm on both days, with an hour's lunch break.
The course will take place in a cluster room, with access to a computer and R.
You're welcome to bring your own laptop if preferred (access to the UCL guest network will also be provided), but make sure R is installed on your laptop before attending (installation guidelines will be made available two weeks before the course).
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
You can request a certificate of attendance for all of our courses once you've completed it. Please send your request to email@example.com
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
Prices include printed course materials, refreshments (and lunch for non-ICH participants).
You can cancel your booking up to five working days before the start of the course for a full refund, but please give as much notice as possible. Places cancelled or changed after this point won't be eligible for a refund. 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.)
Eirini Koutoumanou - Course Lead
Eirini joined GOS ICH in 2008 as the first CASC Teaching Fellow and was promoted to Senior Teaching Fellow in 2014. She has a Bachelor’s degree in Statistics from the Athens University of Economics and Business and a Master's degree in Statistics from Lancaster University, and she's currently studying for a PhD at ICH. Eirini started teaching at ICH straight after her student days, putting into practice and further developing her passion for statistics teaching. She's played an instrumental role in the formation of CASC and hopes to see it develop further.
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.
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Course information last modified: 19 Sep 2019, 09:26