Course Overview

This workshop extends on the Fundamentals of Regression course and introduces multivariate statistics in a model based framework. We move beyond a single response variable to visualising and analysing a collection of correlated response variables. In this course, many of the motivating applications come from ecology, though the methods do generalise to multivariate data in other settings. Methods available to you depend on the number of responses relative to your sample size; and like in univariate regression we also need to think about the response variable type (binary, count etc). There is emphasis on understanding the concepts of statistical procedures (with a minimum of mathematics, although some will be discussed) and on interpreting computer output. It is designed to help you, the researcher. There will be plenty of practical work.

Regression, with normal and non normal responses, and basic R skills are assumed knowledge. These are covered in our R course, Fundamentals of Regression Course and Mixed Models Course. Please note - this course is NOT about regression with multiple predictor variables - for example when many predictor variables might be correlated with your outcome variable. Our brief pre-enrolment questionaire is designed to help you decide if you are ready for this course (https://unswstatscentral.shinyapps.io/Multivariate_Preenrolment ).

Course outline

Introduction to multivariate data – with fewer response variables

What is a multivariate research question
Why use multivariate methods
Covariance matrices
Analysis with manova
Checking model assumptions

Multivariate data – with lots of response variables

Reducing the rank of the covariance matrix
Reduced Rank Analysis with PCA
Reduced Rank Analysis with generalised latent variable models (glmmTMB)
Visualising high dimensional data

Multivariate data – hypothesis testing with LOTS and LOTS of response variables

Design based inference in mvabund
Analysing Compositional data – row effects and offsets
Correlation types

Accessibility

This is an in person course. If you wish to participate, but in person attendance is not accessible to you (e.g. you have hearing or vision impairment, parenting responsibilities, live too far) please email Eve (eve.slavich@unsw.edu.au) to arrange online attendance. The virtual component will be run using Zoom, and closed captions will be activated on request.

Slides are in PDF format, exercises are in R markdown, and both will be downloadable in advance. If HTML slides and alt text are needed to assist accessibility we will make every effort to provide these, please let us know well in advance. Lectures will be recorded and uploaded to YouTube, and available for a week following the workshop. Please email Eve (eve.slavich@unsw.edu.au) with any questions or requests.

Prerequisites: RStudio and Regression (with a single response variable) are assumed knowledge.

Course requirements: You will need to bring and use your own computer during the workshop.

Date: 8 August 2024

Duration: 9.00 - 4:30pm

Delivery Mode: This course will be delivered in-person ONLY!

You will receive a certificate of completion for the course.

Note: If you have a funding support and would like to pay by "Internal Funding Payment", please contact us stats.central@unsw.edu.au

FAQs

How can I contact the organiser with any questions?

Please send us an email at: stats.central@unsw.edu.au