# Chapter 15 Network Analysis tutorial

**Author: Jiaxin Deng**

## 15.1 Brief introduction to network analysis

A network is a set of nodes connected by a set of edges.

Several packages are used in the network analysis, including `network`

, `statnet`

, `igraph`

and `qgraph`

.

`qgraph`

was developed in the context of psychometrics approach by Dr. Sacha Epskamp and colleagues in 2012. For more details, please click this following link for the paper published in *Journal of Statistical Softare*:

https://www.jstatsoft.org/article/view/v048i04

This package can create graphs to visualize the statistics in different layout modes based on different correlation matrices, such as polychoric correlation, partial correlation.

## 15.2 Example code

Here is the following steps to conduct a network analysis using `qgraph`

.

Take `big5`

data as an example. This is a dataset of the Big five personality traits assessed on 500 psychology students.

Firstly, `qgraph`

package should be activated using `library()`

`library(qgraph)`

And then, data need to be imported in the current R project.

`data(big5)`

To creat the graph is basically to use `qgraph()`

, such as:

`qgraph<-qgraph(cor(big5))`

But it should be noted that the input in the `qgraph()`

can be a weight matrix or an edgelist.

Thus, if you want to creat the association network, `cor()`

/`cor_auto()`

can be used to creat the matrix first.

Also, you can use `groups`

to indicate which nodes belong together, such as:

```
data("big5groups")
qgraph(cor(big5), groups=big5groups)
```

Besides, you can use some additional arguments to customize your representing graph.

you can use `layout`

to change the representation, such as:

`qgraph(cor(big5), groups=big5groups,layout= "spring")`

`qgraph(cor(big5), groups=big5groups,layout= "circle")`

## 15.3 Including Plots

You can also embed plots, for example:

Note that the `echo = FALSE`

parameter was added to the code chunk to prevent printing of the R code that generated the plot.