View source: R/multiple_netfacs_network.R
multiple_netfacs_network | R Documentation |
Takes the results of the nefacs object for combinations of 2 elements and
turns them into a network object (class igraph
and
tbl_graph
) that can be used for further plotting and analyses
multiple_netfacs_network( netfacs.list, link = "unweighted", significance = 0.01, min.count = 1, min.prob = 0, ignore.element = NULL ) multiple.netfacs.network( netfacs.list, link = "unweighted", significance = 0.01, min.count = 1, min.prob = 0, ignore.element = NULL )
netfacs.list |
list of multiple objects resulting from
|
link |
determines how nodes/elements are connected. 'unweighted' gives a 1 to significant connections and 0 to all others; 'weighted' gives the difference between observed and expected probability of co-occurrence; 'raw' just uses the observed probability of co-occurrence; 'SRI' uses the simple ratio index/affinity (probability of co-occurrence/ (probabilities of each element and the combination)) |
significance |
numeric value, determining the p-value below which combinations are considered to be dissimilar enough from the null distribution |
min.count |
numeric value, suggesting how many times a combination should at least occur to be displayed |
min.prob |
numeric value, suggesting the probability at which a combination should at least occur to be displayed |
ignore.element |
vector of elements that will not be considered for the network, e.g. because they are too common or too rare or their interpretation is not relevant here |
Function returns a network object where the nodes are the elements, edges represent their co-occurrence, and the vertex and edge attributes contain all additional information from the netfacs object
data(emotions_set) emo.faces <- netfacs_multiple( data = emotions_set[[1]], condition = emotions_set[[2]]$emotion, ran.trials = 10, # only for example combination.size = 2 ) emo.nets <- multiple_netfacs_network(emo.faces)
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