covFX: Generate estimated monadic covariate effects for estimated mmsbm model

Description

The function estimates the effect of a shift in monadic covariate values on the probability of edge formation in the network.

Usage

covFX(fm, cov, shift, max.val = FALSE)

Value

List with named components:

Overall Avg. Effect: Overall average effect of the covariate shift on the predicted probability of edge formation.
Avg. Effect by Time: Vector of average effects of the covariate shift on the predicted probability of edge formation for each time period.
Avg. Effect by Node: Vector of average effects of the covariate shift on the predicted probability of edge formation for each node.
Avg. Effect by Dyad: Vector of average effects of the covariate shift on the predicted probability of edge formation for each node dyad.
Avg. Effect Dyad-Time: Vector of estimated effects of the covariate shift on the predicted probability of edge formation for each node dyad-time unit.

Arguments

fm: An object of class mmsbm, a result of a call to mmsbm.
cov: Character string identifying the monadic covariate to be shifted.
shift: Numeric value specifying the desired increase or decrease in the monadic covariate. The monadic predictor will be shifted by this value for all nodes and time periods.
max.val: An optional numeric value specifying the maximum possible value for the monadic covariate.

Author

Santiago Olivella (olivella@unc.edu), Adeline Lo (aylo@wisc.edu), Tyler Pratt (tyler.pratt@yale.edu), Kosuke Imai (imai@harvard.edu)

Examples

Run this code

library(NetMix)
## Load datasets
data("lazega_dyadic")
data("lazega_monadic")
## Estimate model with 2 groups
lazega_mmsbm <- mmsbm(SocializeWith ~ Coworkers,
                      ~  Age,
                      senderID = "Lawyer1",
                      receiverID = "Lawyer2",
                      nodeID = "Lawyer",
                      data.dyad = lazega_dyadic,
                      data.monad = lazega_monadic,
                      n.blocks = 2,
                      mmsbm.control = list(seed = 123, 
                                           conv_tol = 1e-2, 
                                           hessian = FALSE))

## Compute effect of decreasing every lawyers' age by 10 years
fx_list <- covFX(lazega_mmsbm, cov = "Age", shift = -10)
fx_list[["Overall Avg. Effect of Age"]]

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