homophily_stat {ghypernet} | R Documentation |
Calculate homophily in multi-edge graphs.
Description
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.
Usage
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 |
nodes |
optional character/factor vector. If an edgelist is provided, 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 homophily change statistic matrix. Zero values in the predictors are recognized in the gHypEG regression as structural zeroes. To ensure this does not happen, please recode your zero-values in all your predictors, ideally using a dummy variable fitting an optimal value for the zeroes. Only useful with absdiff type. |
Value
Homophily change statistic matrix.
Author(s)
LB, GC
See Also
reciprocity_stat
or sharedPartner_stat
Examples
homop_stat <- homophily_stat(variable = vertexlabels, nodes = rownames(adj_karate))
nrm(w=list('homophily'= homop_stat), adj_karate, directed = FALSE, selfloops = FALSE)