The function calculates homophily matrices. If you supply a categorical
variable (factor, character), the function returns attribute matches for
dyads from the same group. If you supply a continuous variable (numeric,
integers), the function returns absolute difference effects for each dyad in
the graph.

homophily_stat(
variable = variable,
type = "categorical",
nodes = nodes,
these.categories.only = NULL,
zero_values = NULL
)

## Arguments

variable |
A attribute variable. Can be categorical (attribute matches)
or continuous (absolute difference effects). |

type |
set to `categorical` . Can be set to `absdiff` instead.
If set to `categorical` , the homophily statistic calculates matches
between dyads from the same group (analogous to dummy variables measuring
attribute match between two nodes (=10) and attribute mismatch (=1)). If
set to `absdiff` it calculates the difference in values from variable
for each dyad in the graph. |

nodes |
optional character/factor vector. If an edgelist is provied, you
have to provide a list of unique identifiers of your nodes in the graph.
This is because in the edgelist, isolates are usually not recorded. If you
do not specify isolates in your nodes object, they are excluded from the
analysis (falsifies data). |

these.categories.only |
optional vector specifying the categories to be
used, if only a subset of factor(variable) is needed. |

zero_values |
optional numeric value. Use this to substitute zero-values
in your reciprocity change statistic matrix. Zero values in the predictors
are recognized in the gHypEG regression as structural zeros. To ensure this
does not happen, please recode your zero-values in all your predictors. If
`zero_values` is not specified, the minmal value divided by 10 is used
instead. |

## Value

Homophily change statistic matrix.

## See also