# netfacs.reciprocity: Calculate reciprocity of probabilities that two elements... In NetFACS: Network Applications to Facial Communication Data

 netfacs.reciprocity R Documentation

## Calculate reciprocity of probabilities that two elements appear together

### Description

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].

### Usage

```netfacs.reciprocity(netfacs.data)
```

### Arguments

 `netfacs.data` object resulting from netfacs() function

### Value

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

### Examples

```### 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)
```

NetFACS documentation built on Dec. 7, 2022, 1:12 a.m.