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receive

Source: R/effects.R
receive.Rd

Specifies the statistic for a "receive" effect in the tie-oriented model or the receiver choice step of the actor-oriented model. A "receive" effect refers to an exogenous actor attribute that affects actor i's rate of receiving events.

Usage

receive(variable, attr_actors = NULL, scaling = c("none", "std"), 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.'

scaling

the method for scaling the statistic. Default is to not scale the statistic. Alternatively, standardization of the statistic per time point can be requested with "std".

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 the value of the exogenous attribute for actor i at time t for all dyads in the riskset that have actor i as receiver. Note that a "receive" effect is only defined for directed relational events.

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

data(history)
data(info)

# Tie-oriented model
reh_tie <- remify::remify(history, model = "tie")
effects <- ~ receive("extraversion")
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: receive_extraversion

# Actor-oriented model
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: receive_extraversion