Since October 2009, I have written 13 articles for the R Tutorial Series blog. The first two introduce new users to R. The remaining 11 cover a wide range of topics related to multiple regression and correlation. This collection of tutorials represents...
Say you’ve got a bunch of survival/mortality data from an experiment. Maybe you exposed batches of snails to various high temperatures for a few hours, and recorded the number alive and dead in each batch at the end. Now you’d like to repor...
I forgot to link this up, but I have a new article (joint with our editor) over at Fantasy Ball Junkie. I run an extremely crude model to see if players who were mentioned in the media as having lost weight, gained muscle, gained speed, got eye surgery...
Often times, a scatterplot reveals a pattern that seems not so linear. Polynomial regression can be used to explore a predictor at different levels of curvilinearity. This tutorial will demonstrate how polynomial regression can be used in a hierarchica...
Categorical predictors can be incorporated into regression analysis, provided that they are properly prepared and interpreted. This tutorial will explore how categorical variables can be handled in R.Tutorial FilesBefore we begin, you may want to downl...
Interaction variables introduce an additional level of regression analysis by allowing researchers to explore the synergistic effects of combined predictors. This tutorial will explore how interaction models can be created in R.Tutorial Files Before we...
Regression models can become increasingly complex as more variables are included in an analysis. Furthermore, they can become exceedingly convoluted when things such as polynomials and interactions are explored. Thankfully, once the potential independe...
The commonly applied analysis of variance procedure, or ANOVA, is a breeze to conduct in R. This tutorial will explore how R can be used to perform ANOVA to analyze a single regression model and to compare multiple models.Tutorial FilesBefore we begin,...
Do you need a way to find out which individual variables in R consume the most memory? # create dummy variables for demonstration x <- 1:1000 y <- 1:10000 z <- 1:100000 # print aggregate memory usage statistics print(paste('R is using', mem...
This tutorial demonstrates to the R novice how to create five machine learning models for classification and compare the performance graphically with ROC curves in one chart. For a simpler introduction, start with Plot ROC curve and lift chart in R. # ...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
