`Loading required package: pacman`

# Scoring and Reliability Analysis of Psychometric Network

## Minimal Example

```
exp1 <- matrix(c(
0, .8, .5,
.8, 0, 0.1,
.5, .1, 0
), nrow = 3, ncol = 3, byrow = T)
rownames(exp1) = colnames(exp1) = c("A", "B", "C")
qgraph::qgraph(input = exp1, edge.labels=T, edge.label.cex = 1.7, edge.label.color = "black")
```

The centrality measures for three nodes:

`mykbl(centrality(exp1))`

node | Betweenness | Closeness | Strength | ExpectedInfluence |
---|---|---|---|---|

A | 1.155 | 1.114 | 1.044 | 1.044 |

B | -0.577 | -0.295 | -0.095 | -0.095 |

C | -0.577 | -0.819 | -0.949 | -0.949 |

Assume that there are two individuals with different scores on three items:

```
response <- data.frame(
A = c(1, 5),
B = c(1, 1),
C = c(5, 1)
)
rownames(response) <- c("Person1", "Person2")
mykbl(response)
```

A | B | C | |
---|---|---|---|

Person1 | 1 | 1 | 5 |

Person2 | 5 | 1 | 1 |

We can calculate the weighted network scores for them based on Strength centrality measures and their item scores

The strength-based network score reflect one’s **overall level of clusters of nodes in a network**.