Longitudinal and mixed model analysis using R (QCIF) [webinar]

This is a QCIF course and places are highly limited as Graduate School is paying the fee. If you are unable to attend, please de-register (or email graduateschool@uq.edu.au if you are unable to do so). An unexplained absence could result in all your future QFAB registrations becoming Waitlisted. You may only attend the workshop once. Repeat bookings will be removed and placed on the Waitlist.

Recommended Participants

The hands-on workshop is relevant for all disciplines, although examples and exercises will focus on biological datasets. Researchers who are dealing with longitudinal data and wish to understand how to analyse them effectively. The workshop is relevant for all disciplines, although examples and exercises will focus on biological datasets. Prior expertise with R and the command line interface is required to a level equivalent of that provided by the R for Reproducible Scientific Research workshop, as the basics of R will not be covered. Participants are expected to have a basic familiarity with the concepts of statistical hypothesis testing and regression analysis.

Learning Objectives

• Recognise longitudinal datasets and identify the different types of longitudinal data
• Understand the difference between linear regression and linear mixed models, and know when to apply each
• Generate a range of descriptive statistics for longitudinal data using R
• Chose and apply the appropriate R package for different types of linear mixed model analysis
• Interpret and evaluate the output from R for linear mixed model predictions

Syllabus

●Introduction to principles of longitudinal data analysis

●Introduction to linear mixed models using specific R packages

●Understanding the basics of fixed and random effects, and how to choose them

●Running models in R and interpretation and visualisation from such analyses

Prequisites and pre-workshop preparation

• Prior expertise of R and the command line interface is mandatory as the basics of R will not be covered. Consider attending the Library's R and RStudio workshop or R for Reproducible Scientific Research workshop first.
• Consider attending the Library's R and RStudio course first.
• Participants are expected to have a basic familiarity with the concepts of descriptive statistics and elementary statistical hypothesis testing.
• Participants will need to bring a laptop configured for Eduroam wifi access (https://my.uq.edu.au/information-and-services/information-technology/internet-and-wifi/connecting-wifi) and with R and RStudio installed.