Specifies the statistic for an `degreeMax` effect in the tie-oriented model with undirected events.
Usage
degreeMax(scaling = c("none", "prop", "std"), consider_type = TRUE)Arguments
- scaling
the method for scaling the degree statistic. Default is to not scale the statistic (scaling = "none"). Alternatively, scaling of the raw degree counts by two times the number of past events at time t can be requested with 'prop' or standardization of the raw degree counts per time point can be requested with 'std'.
- consider_type
logical, indicates whether to count the degrees separately for each event type (TRUE, default) or sum degrees across different event types (FALSE).
Details
An degreeMax effect refers to the tendency for dyads to increase their interaction rate if the total degree of the most active actor in the pair increases. The statistic at timepoint t for dyad (i,j) is equal to the maximum of the following two values: the number of events before timepoint t that involved actor i and actor j, respectively. Note that the degreeMax effect is only defined for undirected events.
Optionally, a scaling method can be set with scaling. By scaling the
degree count by the total number of past events, the statistic refers to the
fraction of past events that the most active actor was involved in. At the
first time point, when no events did previously occur, it is assumed that
every actor is equally likely to be involved in an event and the statistic
is set equal to 1/n, where n refers to the number of actors.
See also
degreeDiff, degreeMin or
totaldegreeDyad for other types of degree effects for
undirected events.
Examples
reh_tie <- remify::remify(history, model = "tie", directed = FALSE)
effects <- ~ degreeMax()
remstats(reh = reh_tie, tie_effects = effects)
#> 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: degreeMax