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 regression to each of the subsets. We will consider how to handle this extension using one of the data sets available within the R software package. Read the rest of this entry »
Analysis of Covariance – Extending Simple Linear Regression
April 28th, 2010Two-way Analysis of Variance (ANOVA)
February 15th, 2010The 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. Read the rest of this entry »
One-way ANOVA (cont.)
February 12th, 2010In 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. Read the rest of this entry »
One-way Analysis of Variance (ANOVA)
February 3rd, 2010Analysis 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. Read the rest of this entry »
