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same

Source: R/effects.R
same.Rd

Specifies the statistic for a "same" effect in the tie-oriented model or the receiver choice step of the actor-oriented model. A "same" effect refers to an exogenous actor attribute that affects dyad (i,j)'s rate of interacting (tie-oriented model) or actor j's probability of being chosen as a receiver for the event send by the active sender i at time t (actor-oriented model) based on whether actors i and j have the same value (or not) on this attribute.

Usage

same(variable, attr_actors = NULL, attr_data)

Arguments

variable

string with the name of the column in the attr_actors object for which the statistic has to be computed.

attr_actors

optionally, an object of class data.frame that contains the attribute, see 'Details.'

attr_data

Deprecated argument. Please use 'attr_actors' instead.

Value

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

Details

The statistic at timepoint t is equal to one for dyads (i,j) that have the same value on the attribute at timepoint t (tie-oriented model) or one for receivers j that have the same value on the attribute as the active sender i at timepoint t (actor-oriented model) and equal to 0 for dyads and receivers that do not have the same value.

Construct the `attr_actors` object as a data frame where each row represents the attribute value of actor i at timepoint t:

  • name: The actors' name.

  • time: The time when the attribute values change.

  • variable: The third column contains the attribute used in the specification of the "difference" effect. The column name should correspond to the string supplied to the variable argument in the `difference()` function.

Note that it is possible to omit the `attr_actors` object in the call of difference() and, instead, supply it in the call of remstats() for multiple exogenous effects.

Examples

reh_tie <- remify::remify(history, model = "tie")
effects <- ~ same("age")
remstats(reh = reh_tie, tie_effects = effects, attr_actors = info)
#> Relational Event Network Statistics
#> > Model: tie-oriented
#> > Computation method: per time point
#> > Dimensions: 115 time points x 90 dyads x 2 statistics
#> > Statistics:
#> 	 >> 1: baseline
#> 	 >> 2: same_age

reh_actor <- remify::remify(history, model = "actor")
remstats(reh = reh_actor, receiver_effects = effects, attr_actors = info)
#> Relational Event Network Statistics
#> > Model: actor-oriented
#> > Computation method: per time point
#> > Sender model: empty
#> > Receiver model:
#> 	 >> Dimensions: 115 events x 10 actors x 1 statistics
#> 	 >> Statistics:
#> 	 	 >>> 1: same_age