migraph (version 0.7.1)

netlm: Linear regression for multimodal network data

Description

This function extends the multiple regression quadratic assignment procedure (MRQAP) of network linear model to two mode networks.

Usage

netlm(formula, data, ...)
# S3 method for netlm
summary(object, reps = 1000, ...)
# S3 method for summary.netlm
print(
  x,
  digits = max(3, getOption("digits") - 3),
  signif.stars = getOption("show.signif.stars"),
  ...
)

Arguments

formula

A formula describing the relationship being tested.

data

A named list of matrices, graphs, or a tidygraph object.

...

Arguments passed on to lm().

object

an object of class "netlm", usually as a result of a call to netlm().

reps

Integer indicating the number of draws to use for quantile estimation. (Relevant to the null hypothesis test only - the analysis itself is unaffected by this parameter.) Note that, as for all Monte Carlo procedures, convergence is slower for more extreme quantiles. By default, reps=1000.

x

an object of class "summary.netlm", usually, a result of a call to summary.netlm().

digits

the number of significant digits to use when printing.

signif.stars

logical. If TRUE, <U+2018>significance stars<U+2019> are printed for each coefficient.

Examples

# NOT RUN {
mat1 <- matrix(c(0,1,1,0,0,1,1,1),4,2)
mat2 <- matrix(c(0,1,0,1,0,1,0,1),4,2)
mat3 <- matrix(c(0,0,1,1,0,0,1,1),4,2)
lmat <- list(mat1 = mat1, mat2 = mat2, mat3 = mat3)
model1 <- netlm(mat1 ~ mat2 + mat3, lmat)
summary(model1)
# }