Course Overview

This course provides a comprehensive hands-on introduction to regression analysis techniques The course content is designed for researchers with some prior knowledge of basic statistical testing, such as t-tests, p-values, confidence intervals and simple linear regression. The primary focus is on developing a conceptual understanding of regression models through numerous examples. There will be a strong emphasis on practical implementation in R, and interpretation of output. Approximately half the time will be dedicated to practical hands-on sessions.

The core content starts from linear models with more than one variable, enabling research questions like "What is the effect of this treatment/intervention after adjusting for confounding variables?" or "What is the relationship between two variables while controlling for other factors?" We then cover interactions between variables in linear models, enabling research questions like: "How does the effect of the treatment depend on some other variable? Is the treatment effect different between groups?" and "How is the relationship between two variables modified by some other variable?"

Fundamental regression concepts and skills that arise in regression, like multicollinearity, multiple testing, model selection, generalising the linear model to data that is non-normal (e.g., binary response and count data), are all covered in this course. By the end of this course, you will have a foundation in regression modelling techniques with the practical experience in R needed for more advanced regression methods like mixed models, longitudinal data analysis, survival analysis, meta-analysis, generalised additive models, multivariate analysis, ordinal and multinomial regression, spatial regression and other extensions.

Course outline

Day 1: Revision, Multiple Regression Introduction and Extensions

Day 2: Morning/Afternoon: Multiple Comparisons/Model Selection

Day 3: Morning/Afternoon: Generalized Linear Models (GLMs)/Generalized Additive Models (GAMs)

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

Presenter and Expertise: Eve Slavich, Statistical Consultant, UNSW Stats Central

Date: Tuesday 11 to Thursday 13 February 2025

Duration: 9.30am - 4.00pm, each day

Delivery Mode: In-Person ONLY

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