Testing the omnibus hypothesis via one-way ANOVA is simple process in R. This tutorial will explore how R can be used to perform a one-way ANOVA to test the difference between two (or more) group means.Tutorial FilesBefore we begin, you may want to dow...
Two way analysis of variance models can be fitted to data using the R Commander GUI. The general approach is similar to fitting the other types of model in R Commander described in previous posts. Fast Tube by Casper The “Statistics” menu provides access to some analysis of variance models via the “Means” sub-menu: Multi-way ANOVA – the
One way analysis of variance models can be fitted to data using the R Commander GUI. The general approach is similar to fitting the other types of model in R Commander described in previous posts. Fast Tube by Casper The “Statistics” menu provides access to some analysis of variance models via the “Means” sub-menu: One-way ANOVA – the
The simple linear regression model considers the relationship between two variables and in many cases more information will be available that can be used to extend the model. For example, there might be a categorical variable (sometimes known as a covariate) that can be used to divide the data set to fit a separate linear
Repeated measures ANOVA is a common task for the data analyst. There are (at least) two ways of performing “repeated measures ANOVA” using R but none is really trivial, and each way has it’s own complication/pitfalls (explanation/solution to which I was usually able to find through searching in the R-help mailing list). So for future reference, I am starting this page...
I needed to produce a few a interaction plots for my book in R and, while the interaction.plot() function is useful it has a couple of drawbacks. First, the default output isn't very pretty. Second, it works from the raw data, whereas I often need plot...
My goal in this post is to give an overview of Friedman’s Test and then offer R code to perform post hoc analysis on Friedman’s Test results. (The R function can be downloaded from here) Preface: What is Friedman’s Test Friedman test is a non-parametric randomized block analysis of variance. Which is to say it is a non-parametric version of...
The analysis of variance (ANOVA) model can be extended from making a comparison between multiple groups to take into account additional factors in an experiment. The simplest extension is from one-way to two-way ANOVA where a second factor is included in the model as well as a potential interaction between the two factors. As an example
In a previous post we considered using R to fit one-way ANOVA models to data. In this post we consider a few additional ways that we can look at the analysis. In the analysis we made use of the linear model function lm and the analysis could be conducted using the aov function. The code used
Analysis of Variance (ANOVA) is a commonly used statistical technique for investigating data by comparing the means of subsets of the data. The base case is the one-way ANOVA which is an extension of two-sample t test for independent groups covering situations where there are more than two groups being compared. In one-way ANOVA the data
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
