influenceTable: Function to construct influence tables for SAOMs

In RSiena: Siena - Simulation Investigation for Empirical Network Analysis

Function to construct influence tables for SAOMs

Description

The function influenceTable constructs influence tables which may be helpful for the interpretation of results for network and behavior dynamics, for an estimation result represented by a sienaFit object created by siena07.

Usage

influenceTable(x, xd, netname, behname,
    as.matrix=FALSE, levls=NULL, levls.alt=levls,
    out.ego=1, silent=FALSE, nfirst=x$nwarm+1,
    include.endow=FALSE, include.creation=FALSE)

Arguments

x	An object of class sienaFit, produced by a call to siena07 for a model including a behavioral dependent variable; or an object of class sienaMeta, produced by a call to siena08; or an object of class sienaBayesFit, produced by a call to sienaBayes.
xd	If x is of class sienaFit, a siena data set used to produce x. If x is of class sienaMeta or sienaBayesFit, one of the data sets used to produce x; preferable a representative one.
netname	character string: name of network dependent variable.
behname	character string: name of behavior dependent variable.
as.matrix	boolean: will the table be returned as a matrix.
levls	levels for ego.
levls.alt	levels for alter.
out.ego	presumed outdegree of ego for effects totSim and totAlt.
silent	boolean; if FALSE, the parameters taken from x are reproduced at the console.
nfirst	If x is of class sienaBayesFit: first run in posterior sample used for constructing the table.
include.endow	boolean, used only for models utilizing influence and endowment effects: by specifying include.endow=TRUE, # the sum of evaluation and endowment effects is used.
include.creation	boolean, used only for models utilizing influence and creation effects: by specifying include.creation=TRUE, # the sum of evaluation and creation effects is used.

Details

This functions is used for constructing influence tables for the interpretation of results for network and behavior dynamics obtained with the RSiena or multiSiena packages.

In matrix form, each row corresponds to a given average behavior of the alters, to whom the focal actor (ego) is connected by an outgoing tie; the columns are the different potential values of ego’s own behavior. The rows are for the values in levls.alt, the columns for the values in levls.

If levls is NULL (the default), the levels of ego's behavior are taken as the integer range of the dependent actor variable. In most applications levls.alt will be the same as levls, in which case it does not have to be specified.

The data set xd is only used to get means and ranges which are used somewhere in the effects.

This function has its own print method.

Value

An object of class influenceTable.
This represents the joint contribution to the evaluation function of effects "linear", "quad", "avAlt", "avSim", "totAlt", "totSim", "avAttHigher", "avAttLower", "threshold", "threshold2", "threshold3", and "threshold4".
If as.matrix=TRUE, the object is a matrix; if as.matrix=FALSE (the default), it is a data frame, where the rows are all combinations of levls and levls.alt, and the columns:

alter	alter's values as a factor;
zalter	the values levls.alt
zego	the values levls
select	the value of the influence table.

Author(s)

Tom Snijders

References

https://www.stats.ox.ac.uk/~snijders/siena/
See the manual, Sections 13.2 and 13.4.

See Also

siena07, siena08

Examples

mynet <- sienaDependent(array(c(s501, s502), dim=c(50, 50, 2)))
mybeh  <- sienaDependent(s50a[,1:2], type="behavior")
mydata <- sienaDataCreate(mynet, mybeh)
myeff <- getEffects(mydata)
myeff <- includeEffects(myeff, avAlt, name="mybeh", interaction1="mynet")
myalgorithm <- sienaAlgorithmCreate(nsub=2, n3=100, seed=1291)
# nsub=2, n3=100 is used here for having a brief computation, not for practice.
ans <- siena07(myalgorithm, data=mydata, effects=myeff, silent=TRUE, batch=TRUE)
influenceTable(ans, mydata, "mynet", "mybeh")

RSiena documentation built on Aug. 8, 2025, 6:05 p.m.