# interactions

## Logistic Regression in R

Introduction In this post, I’ll introduce the logistic regression model in a semi-formal, fancy way. Then, I’ll generate data from some simple models: 1 quantitative predictor 1 categorical predictor 2 quantitative predictors 1 quantitative predictor with a quadratic term I’ll model data from each example using linear and logistic regression. Throughout the post, I’ll explain equations, terms, output, and plots. Here are some key takeaways:

## Testing Conditional Indirect Effects/Mediation in R

This post builds on a previous post on Testing Indirect Effects/Mediation in R. What is mediation? There are many ways to define mediation and mediators. Here’s one way: Mediation is the process by which one variable transmits an effect onto another through one or more mediating variables. For example, as room temperature increases, people get thirstier, and then they drink more water. In this case, thirst transmits the effect of room temperature on water drinking.

## Probing and Plotting Interactions in R

What is moderation? Moderation refers to how some variable modifies the direction or the strength of the association between two variables. In other words, a moderator variable qualifies the relation between two variables. A moderator is not a part of some proposed causal process; instead, it interacts with the relation between two variables in such a way that their relation is stronger, weaker, or opposite in direction—depending on values of the moderator.