geeNET: geeNET

In MilesOtt/geeNET: geeNET: Weighted GEE for Social Network Data

Description

Fits GEE for data with Network Correlation structures

Usage

geeNET(form, link, adj.matrix, dataset, SE = "sandwich", wt = NULL,
  toep = 1)

Arguments

form	the formula for the model to be fit, like in the lm function
link	link between xbeta and the mean, identity for normal, logit for logistic, Poissonlog for Poisson with log link, Gammalog for gamma with log link
adj.matrix	adjacency matrix of the network
dataset	name of the dataset used for the model
SE	choose either the sandwich or model.based SE estimator
wt	is the vector of inverse probability weights, defaults to NULL which will give all observations equal weights
toep	number of rhos to estimate 1-4 currently are the options for this

Value

standard regression table output

MilesOtt/geeNET documentation built on Aug. 8, 2021, 7:31 p.m.