Course Overview

Date: 12 - 13 May
Time: 9.30am to 4.00pm - each day
Delivery Mode: In-person only
Location: UNSW Sydney, Kensington Campus
Course Pre-requisite:
- Ability to run, check, and interpret linear and generalised linear models in R.

You will received a certificate of completion for the course.

Simple statistical methods (t-tests, chi-square tests, linear models/regression) assume independence of observations and cannot be used when dependence is present in the sample. Mixed models are extensions of linear models to dependent data. Common reasons for dependence are:

• Clustering e.g. multiple patients per hospital, multiple plants per site, multiple measurements on the same individual

• Time and Space - measurements taken close in time and space are more similar (dependent)

In this course we will teach mixed models as a straightforward extension of (generalised) linear models. The course will include lectures and practical sessions, and explain how to fit, check, interpret and communicate results from mixed models.

Register here