For all dyadic combinations that ever appear, this function calculates how reciprocal the conditional probabilities (i.e. probability of A given B, and B given A) of the two elements are. Combinations that are highly reciprocal indicate that the two elements always occur together and might represent a fixed combination, while low reciprocity might indicate that one element is an extension of the other. Values approaching -1 indicate that one element is strongly dependent on the other, but this is not reciprocated; values around 0 indicate that neither is conditional on the other; and values approaching 1 indicate that both values are conditional on each other. If P[A|B] is the larger conditional probability, the reciprocity is calculated as reciprocity = ((P[B|A]/P[A|B]) - (P[A|B] - P[B|A])) * P[A|B].
object resulting from netfacs() function
Function returns a data frame with each combination, the reciprocity of conditional occurrence from -1 (one element entirely depends on the other, but not vice versa) to 1 (both elements always occur together)
The directions and conditional probabilities of both elements are also returned
### how do angry facial expressions differ from non-angry ones? data(emotions_set) angry.face <- netfacs( data = emotions_set[], condition = emotions_set[]$emotion, test.condition = "anger", ran.trials = 100, combination.size = 2 ) netfacs.reciprocity(angry.face)
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