# Regression

### Incorporating Graphs in Regression Diagnostics with Stata

May 24th, 2016 by

You put a lot of work into preparing and cleaning your data. Running the model is the moment of excitement.

You look at your tables and interpret the results. But first you remember that one or more variables had a few outliers. Did these outliers impact your results? (more…)

### Member Training: Transformations & Nonlinear Effects in Linear Models

May 7th, 2015 by

Why is it we can model non-linear effects in linear regression?

What the heck does it mean for a model to be “linear in the parameters?” (more…)

### Linear Models in R: Improving Our Regression Model

April 23rd, 2015 by

Last time we created two variables and used the lm() command to perform a least squares regression on them, and diagnosing our regression using the plot() command.

Just as we did last time, we perform the regression using lm(). This time we store it as an object M. (more…)

### Linear Models in R: Diagnosing Our Regression Model

April 21st, 2015 by

by David Lillis, Ph.D.

Last time we created two variables and added a best-fit regression line to our plot of the variables. Here are the two variables again. (more…)

### Linear Models in R: Plotting Regression Lines

April 10th, 2015 by

Today let’s re-create two variables and see how to plot them and include a regression line. We take height to be a variable that describes the heights (in cm) of ten people. (more…)

### Spotlight Analysis for Interpreting Interactions

July 21st, 2014 by

Not too long ago, a client asked for help with using Spotlight Analysis to interpret an interaction in a regression model.

Spotlight Analysis? I had never heard of it.

As it turns out, it’s a (snazzy) new name for an old way of interpreting an interaction between a continuous and a categorical grouping variable in a regression model. (more…)