Generalised linear models (IN-PERSON)

Intermediate

Generalised linear models are the kind of models we would use if we had to deal with non-continuous response variables. For example, this happens if you have count data or a binary outcome.

This course aims to introduce generalised linear models, using the R software environment. Similar to Core statistics using R this course addresses the practical aspects of using these models, so you can explore real-life issues in the biological sciences. The Generalised linear models using R course builds heavily on the knowledge gained in the core statistics sessions, which means that the Core statistics using R course is a firm prerequisite for joining.

There are several aims to this course:

1. Be able to distinguish between linear models and generalised linear models

2. Analyse binary outcome and count data using R

3. Critically assess model fit

R is an open-source programming language so all of the software we will use in the course is free. We will be using the R Studio interface throughout the course. Most of the code will be focussed around the tidyverse and tidymodels packages, so a basic understanding of the tidyverse syntax is essential.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• ♿ The training might take place at the Craik-Marshall training room. This is located on the first floor and there is currently no wheelchair or level access. Please put level access requirements in the "Special requirements" section, so we can take that into consideration when allocating the room.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• This course is - in abbreviated form - included as part of several DTP and MPhil programmes, as well as other departmental training within the University of Cambridge (potentially under a different name) so participants who have attended statistics training elsewhere should check before applying.

• This course requires users to be familiar with the R language. Attending an introductory course Introduction to R for biologists is advantageous if you do not have a working knowledge of R already.
• Participants need to have attended the Core statistics using R course.
• Familiarity with the tidyverse syntax is essential.

If you are unsure whether you have sufficient knowledge, please do not hesitate to contact us and we will be able to discuss this.

Number of sessions: 1

During this course you will learn about:

• Analysing binary and proportional responses data using logistic regression
• Analysing count data using Poisson regressions
• Assess model fit

After this course you should be able to:

• Analyse non-continuous response variables using generalised linear models
• Critically assess if the model is appropriate and well-specified

The course is based around computer practicals interspersed with short presentations used to explain core ideas and principles.

This course will require you to have an up-to-date installation of R and RStudio on your computer beforehand. Brief installation guides will be provided, and support will be available from the tutors during the sessions. Participants must have their own computers to work on.

• Free for registered University of Cambridge students
• £ 60/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 60/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 120/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

1

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