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Specifies the statistic for a shared partners effect for undirected events.

Usage

sp(unique = FALSE, scaling = c("none", "std"), consider_type = TRUE)

Arguments

unique

A logical value indicating whether to sum the minimum of events with third actors (FALSE, default) or the number of third actors that create a new, unique shared partner (TRUE). See details for more information.

scaling

the method for scaling the triad statistic. Default is to not scale the statistic but keep the raw 'counts'. Alternatively, standardization of the raw counts per time point can be requested with 'std'.

consider_type

logical, indicates whether to count the shared partners separately for each event type (TRUE, default) or sum across different event types (FALSE).

Value

List with all information required by `remstats::remstats()` to compute the statistic.

Details

The shared partners effect describes the propensity of dyads to interact based on the number of past shared partners between them. By default, the statistic at timepoint t for the undirected dyad (i,j) is computed as the sum of the minimum occurrences of past undirected (i,h) and undirected (j,h) events across all actors h.

When the unique parameter is set to TRUE, a different approach is taken. In this case, the statistic counts the number of actors h that contribute to the creation of a new, distinct shared partner between actors i and j.

Additionally, it is possible to specify a scaling method using the scaling parameter.

Please note that the shared partners effect, 'sp', is exclusively defined for undirected events.

See also

otp, itp, osp, or isp for triadic effects for directed relational events.

Examples

reh_tie <- remify::remify(history, model = "tie", directed = FALSE)
effects <- ~ sp()
remstats(tie_effects = effects, reh = reh_tie)
#> Relational Event Network Statistics
#> > Model: tie-oriented
#> > Computation method: per time point
#> > Dimensions: 115 time points x 45 dyads x 2 statistics
#> > Statistics:
#> 	 >> 1: baseline
#> 	 >> 2: sp