index.qmd

---
title: "Mediation, Moderation, and Conditional Process Analysis with R"
author: Dr. Nicola Righetti, PhD
---

## Aims, contents and method of the course

This data analysis seminar focuses on linear regression analysis to explore questions about mediated and moderated effects.

Computer applications will focus on R statistical language, the Rstudio environment ([https://www.rstudio.com](https://www.rstudio.com/)) and the PROCESS software by Andrew F. Hayes ([http://processmacro.org](http://processmacro.org/)).

## Learning outcomes

By the conclusion of this course, students should be proficient in:

-   Executing and comprehending the outcomes of linear regression, moderation, mediation, and conditional process models.

-   Statistically testing competing theories of mechanisms through the evaluation of indirect effects in models that encompass multiple mediators.

-   Representing and investigating interactions in regression models to accurately interpret interaction effects.

-   Calculating and inferring about conditional indirect effects to estimate the contingencies of mechanisms.

-   Utilizing the R language and PROCESS to conduct, depict, and comprehend linear regression, moderation, mediation, and conditional process models.

## Handbook

The handbook of the course and the primary source of most of the material here presented is:

Andrew F. Hayes. [Introduction to Mediation, Moderation, and Conditional Process Analysis. A Regression-Based Approach](https://books.google.at/books?id=6uk7DwAAQBAJ&printsec=frontcover&dq=introduction+to+Mediation,+Moderation,+and+Conditional+Process+Analysis.+A+Regression-Based+Approach.+2018+second+edition&hl=en&sa=X&ved=2ahUKEwjaoLSi6cf9AhV0S_EDHbngDwwQ6AF6BAgHEAI#v=onepage&q=introduction%20to%20Mediation%2C%20Moderation%2C%20and%20Conditional%20Process%20Analysis.%20A%20Regression-Based%20Approach.%202018%20second%20edition&f=false). 2018. SECOND EDITION. THE GUILFORD PRESS, New York, London.