week5_program.Rmd

# Week 5 - Overview

**Lecture**

```{r}
knitr::include_url("https://www.youtube.com/embed/xg84x9BVHAI")
```

**Note that this is a more recent version of the slides than used in the video. The material in the video is sufficient to pass the course.**

[Download slides](pdfs/tcsm_week_5.pdf)

Introducing means into statistical models/How can I investigate mediation?

**Homework for the lecture Mediation:**

Researchers often have theories about possible causal relationships between variables. A particularly important topic in this respect is mediation, in which variable X influences variable Y through a third variable, the mediator. For instance, psychotherapy (X), may affect thoughts (mediator), which in turn affects mood (Y). 

Read this week’s literature and finish the reading questions before coming to the lecture.
- MacKinnen, D. P., Krull, J. L., Lockwood, C. M. (2000). Equivalence of the mediation, confounding, and suppression effect. Prevention Science, 1, 173-181.
- Holbert, R. L. & Stephenson, M. T. (2003). The importance of indirect effects in media effects research: Testing for mediation in structural equation modeling. Journal of Broadcasting & Electronic Media, 47, 556-572.

**Lecture Mediation:**

There are two approaches to investigating mediation. The first approach is within the context of multiple linear regression analysis. The second approach is based on path models, which form a special case of Structural Equation Modeling. We consider both and discuss their advantages and weaknesses.

**Homework for the practical Mediation:**

Perform take home exercise mediation before coming to the practical.
	
**Practical Mediation:**

During the practical we will discuss take home exercise mediation. In the remainder of the practical an introduction into estimating mediation and path models in lavaan will be given.