Faux dixon High School as a network object
This data set represents a simulation of a directed in-school friendship network. The network is named faux.dixon.high.
data(faux.dixon.high)
faux.dixon.high
is a network
object
with 248 vertices (students, in this case) and 1197 directed edges
(friendship nominations). To obtain additional summary information about it,
type summary(faux.dixon.high)
.
The vertex attributes are Grade
, Sex
, and Race
. The
Grade
attribute has values 7 through 12, indicating each student's
grade in school. The Race
attribute is based on the answers to two
questions, one on Hispanic identity and one on race, and takes six possible
values: White (non-Hisp.), Black (non-Hisp.), Hispanic, Asian (non-Hisp.),
Native American, and Other (non-Hisp.)
If the source of the data set does not specified otherwise, this data set is protected by the Creative Commons License https://creativecommons.org/licenses/by-nc-nd/2.5/.
When publishing results obtained using this data set, the original authors (Resnick et al, 1997) should be cited. In addition this package should be cited as:
Mark S. Handcock, David R. Hunter, Carter T. Butts, Steven M. Goodreau, and
Martina Morris. 2003 statnet: Software tools for the Statistical
Modeling of Network Data
https://statnet.org.
The data set is simulation based upon an ergm model fit to data from one school community from the AddHealth Study, Wave I (Resnick et al., 1997). It was constructed as follows:
The school in question (a single school with 7th through 12th grades) was selected from the Add Health "structure files." Documentation on these files can be found here: https://addhealth.cpc.unc.edu/documentation/codebooks/.
The stucture file contains directed out-ties representing each instance of a student who named another student as a friend. Students could nominate up to 5 male and 5 female friends. Note that registered students who did not take the AddHealth survey or who were not listed by name on the schools' student roster are not included in the stucture files. In addition, we removed any students with missing values for race, grade or sex.
The following ergm
model was fit to the original data:
dixon.fit <- ergm(original.net ~ edges + mutual + absdiff("grade") + nodefactor("race", base=5) + nodefactor("grade", base=3) + nodefactor("sex") + nodematch("race", diff = TRUE) + nodematch("grade", diff = TRUE) + nodematch("sex", diff = FALSE) + idegree(0:1) + odegree(0:1) + gwesp(0.1,fixed=T), constraints = ~bd(maxout=10), control = control.ergm(MCMLE.steplength = .25, MCMC.burnin = 100000, MCMC.interval = 10000, MCMC.samplesize = 2500, MCMLE.maxit = 100), verbose=T)
Then the faux.dixon.high dataset was created by simulating a single network from the above model fit:
faux.dixon.high <- simulate(dixon.fit, nsim=1, burnin=1e+8, constraint = "edges")
Resnick M.D., Bearman, P.S., Blum R.W. et al. (1997). Protecting adolescents from harm. Findings from the National Longitudinal Study on Adolescent Health, Journal of the American Medical Association, 278: 823-32.
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