net.loads {EGAnet} | R Documentation |

Computes the between- and within-community
`strength`

of each item
for each community. This function uses the
`comcat`

and
`stable`

functions to calculate
the between- and within-community strength of each item, respectively.

```
net.loads(A, wc, pos.manifold = FALSE, min.load = 0, plot.NL = FALSE)
```

`A` |
Matrix, data frame, or |

`wc` |
Numeric or character vector.
A vector of community assignments.
If input into |

`pos.manifold` |
Boolean.
Should a positive manifold be applied (i.e., should
all dimensions be positively correlated)?
Defaults to |

`min.load` |
Numeric.
Sets the minimum loading allowed in the standardized
network loading matrix. Values equal or greater than
the minimum loading are kept in the output. Values
less than the minimum loading are removed. This matrix can
be viewed using |

`plot.NL` |
Boolean.
Should proportional loadings be plotted?
Defaults to |

Simulation studies have demonstrated that a node's strength centrality is roughly equivalent to factor loadings (Christensen, Golino, & Silvia, 2019; Hallquist, Wright, & Molenaar, in press). Hallquist and colleagues (in press) found that node strength represented a combination of dominant and cross-factor loadings. This function computes each node's strength within each specified dimension, providing a rough equivalent to factor loadings (including cross-loadings).

For more details, type `vignette("Network_Scores")`

Returns a list containing:

`unstd` |
A matrix of the unstandardized within- and between-community strength values for each node |

`std` |
A matrix of the standardized within- and between-community strength values for each node |

`minLoad` |
The minimum loading to appear in summary of network loadings.
Use |

`plot` |
A |

Alexander P. Christensen <alexpaulchristensen@gmail.com> and Hudson Golino <hfg9s at virginia.edu>

Christensen, A. P., & Golino, H. (2021).
On the equivalency of factor and network loadings.
*Behavior Research Methods*, *53*, 1563-1580.

Christensen, A. P., Golino, H., & Silvia, P. J. (2020).
A psychometric network perspective on the validity and validation of personality trait questionnaires.
*European Journal of Personality*, *34*, 1095-1108.

Hallquist, M., Wright, A. C. G., & Molenaar, P. C. M. (2019).
Problems with centrality measures in psychopathology symptom networks: Why network psychometrics cannot escape psychometric theory.
*Multivariate Behavioral Research*, 1-25.

```
# Load data
wmt <- wmt2[,7:24]
## Not run:
# Estimate EGA
ega.wmt <- EGA(wmt)
## End(Not run)
# Network loadings
net.loads(ega.wmt)
```

[Package *EGAnet* version 1.1.0 Index]