Advanced Regression Analysis with R

Advanced Regression Analysis with R#

Overview#

Welcome to Advanced Regression Analysis with R. Our aim is to build on your existing knowledge of regression to fit more complex models that can handle more complicated data sets. In this session you will learn about different types of regression analysis, when to use them and how to interpret the results.

Course Objectives#

  • Use regression answer to answer a wide range of research questions.

  • Be able to fit a regression model with interactions between predictor variables.

  • Be able to fit multi-level regression models.

  • Be able to extract and summarise the results from a range of regression models.

  • Be able to design a regression model appropriate for addressing their specific research question.

Pre-requisite Knowledge#

This course will not include an introduction to R, or how to setup and use R or Rstudio. It is assumed you are comfortable coding in R and are familiar with:

  • how to write and execute commands in the R console

  • what type of variables are available in R and how to work with these

We also assume that you are comfortable with fitting in R and interpreting the output of:

  • simple linear regression

  • multiple linear regression with categorical, binary or continuous predictor variables

  • logistic regression

If not we recommend that you consult our pre-requisite course Introductory Regression Analysis with R.

Install necessary R packages#

There are three packages need for this workshop. The first two (devtools & learnr) are available from CRAN. The third is a package we have developed with the course materials in and is available from GitHub (cfrrRTutorials).

This code will install these three packages.

install.packages("devtools") 
install.packages("learnr") 
library(devtools)
devtools::install_github("ejh243/cfrr-r-tutorials")