linear model

R is Not So Hard! A Tutorial, Part 2: Variable Creation

by David Lillis, Ph.D.

In Part 1 we installed R and used it to create a variable and summarize it using a few simple commands. Today let’s re-create that variable and also create a second variable, and see what we can do with them.

As before, we take height to be a variable that describes the heights (in cm) of ten people. Type the following code to the R command line to create this variable.

height = c(176, 154, 138, 196, 132, 176, 181, 169, 150, 175)

Now let’s take weight to be a variable that describes the weights (in kg) of [Read more...] about R is Not So Hard! A Tutorial, Part 2: Variable Creation

Assumptions of Linear Models are about Residuals, not the Response Variable

by Karen Grace-Martin 6 Comments

I recently received a great question in a comment about whether the assumptions of normality, constant variance, and independence in linear models are about the residuals or the response variable.

The asker had a situation where Y, the response, was not normally distributed, but the residuals were.

Quick Answer: It’s just the residuals.

In fact, if you look at any (good) statistics textbook on linear models, you’ll see below the model, stating the assumptions: [Read more…] about Assumptions of Linear Models are about Residuals, not the Response Variable

Random Intercept and Random Slope Models Webinar

by Karen Grace-Martin 2 Comments

This page is out-of-date.

Please go to the newer version of the page: Random Intercept and Random Slope Models COSA webinar.

The Assumptions of Linear Models: Explicit and Implicit

by Karen Grace-Martin 4 Comments

If you’ve compared two textbooks on linear models, chances are, you’ve seen two different lists of assumptions.

I’ve spent a lot of time trying to get to the bottom of this, and I think it comes down to a few things.

1. There are four assumptions that are explicitly stated along with the model, and some authors stop there.

2. Some authors are writing for introductory classes, and rightfully so, don’t want to confuse students with too many abstract, and sometimes untestable, [Read more…] about The Assumptions of Linear Models: Explicit and Implicit