tie

Specifies the statistic for a "tie" (or, "dyad") effect.

Usage

tie(variable, attr_dyads = NULL, scaling = c("none", "std"), x, variableName)

Arguments

variable

A string specifying the attribute to compute the statistic. If attr_dyads is a data.frame, this refers to the column name in attr_actors. If attr_dyads is a matrix, this corresponds to the name of the exogenous attribute, used to label the statistic in the resulting remstats object.

attr_dyads

A data.frame or matrix containing attribute information for dyads. If attr_dyads is a data.frame, the first two columns should represent "actor1" and "actor2" (for directed events, "actor1" corresponds to the sender, and "actor2" corresponds to the receiver). Additional columns can represent dyads' exogenous attributes. If attributes vary over time, include a column named "time". If attr_dyads is a matrix, the rows correspond to "actor1", columns to "actor2", and cells contain dyads' exogenous attributes.

scaling

The method for scaling the statistic. The default is no scaling. Alternatively, standardization of the statistic per time point can be requested with "std".

x

Deprecated argument. Please use 'attr_dyads' instead.

variableName

Deprecated argument. Please use 'variable' instead.

Value

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

Details

The "tie" effect or "dyad" effect refers to an exogenous dyad attribute that influences dyad (i,j)'s interaction rate (in tie-oriented models) or the probability of actor j being chosen as a receiver for the event sent by the active sender i (in actor-oriented models). The statistic represents the value of the exogenous attribute for dyad (i,j) in the attr_dyads data.

Examples

data(history)
data(both_male_long)
effect <- ~ tie(variable = "both_male", attr_dyads = both_male_long)
reh <- remify::remify(history, model = "tie")
remstats(reh = reh, tie_effects = effect)
#> 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: tie_both_male

data(both_male_wide)
effect <- ~ tie(variable = "both_male", attr_dyads = both_male_wide)
reh <- remify::remify(history, model = "tie")
remstats(reh = reh, tie_effects = effect)
#> 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: tie_both_male