Linear Models 1: Linear regression, ANOVA, ANCOVA and repeated measures (a simple mixed model) focuses on Practical Data Analysis by presenting Statistical Workflows applicable in any software for 4 of the most common univariate analyses: linear regression, ANOVA, ANCOVA, and repeated measures (a simple mixed model). All assuming a normal (gaussian) residual. These workflows can be easily extended to more complex models. The R code used to create output is also included. ​

This is one of 3 workshops for researchers interested in statistical methods such as linear regression, ANOVA, ANCOVA, mixed models, logistic/binary and count (Poisson) regression. Each one builds on the preceding workshops and together they show how all these analyses can be performed using the same easy to understand Generalised Linear Mixed Model (GLMM) framework and workflow. As well as how they 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. There is also a 4th complementary workshop called Statistical Model Building which we recommend for those experienced with Linear Models or who have done at least the first 2 of our workshops.

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:

You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus.

In person @Camden: Choose the "In person" ticket option.

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

• Open to: Academic and Professional Staff, research students, and affiliates of The University of Sydney (with a valid UniKey)
• 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!