Linear Models 2: Logistic and Poisson/count regression-an introduction to Generalised Linear Models (GLM), focuses on Practical data analysis by presenting statistical workflows applicable in any software for two of the more common GLMM’s: Logistic regression for binary data (using a Binomial distribution); and Poisson/count regression for count data (using a Poisson distribution). The GLM framework is also described in detail. The R code used to create output is also included.
This is the second in a series of workshops for researchers interested in statistical methods such as linear regression, ANOVA, ANCOVA, mixed models, logistic and count (Poisson) regression. We will show how all of these analyses can be performed using the same easy to understand Generalised Linear Model framework (GLM). As well as how these methods can be used to analyse experimental designs such as Control vs Treatment, Randomised Control Trials (RCT’s), Before After Control Impact (BACI) analysis, repeated measures plus many more.
The material is organised around statistical workflows applicable in any software that give step by step instructions on how to do the analysis including assumption testing, model interpretation and presentation of results.
Attendance options:
In person: not available for this event.
Online: Choose the "Online Zoom" ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date.
Sydney Informatics Hub
- Please use your University of Sydney email address to register i.e. @sydney.edu.au, @uni.sydney.edu.au, etc
- If you do not have a UniKey, please contact us to confirm your position after registration.
- Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you!!!
