Description Usage Format Licenses and Citation Source References See Also
This data set (formerly called "fauxhigh") represents a simulation of
an in-school friendship network. The network is named faux.mesa.high
because the school community on which it is based is in the rural western
US, with a student body that is largely Hispanic and Native American.
1 |
faux.mesa.high
is a network
object
with 205 vertices (students, in this case) and 203 undirected edges (mutual
friendships). To obtain additional summary information about it, type
summary(faux.mesa.high)
.
The vertex attributes are:
Grade
– attribute has values 7 through 12, indicating each student's
grade in school
Sex
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 section Source of this page does not specify otherwise, this data set is protected by the Creative Commons License https://creativecommons.org/licenses/by/4.0/.
When publishing results obtained using this data set, the original authors
(see sections Source and/or References) should be cited, along with this
R
package. To cite this package please use the following:
Handcock M, Hunter D, Butts C, Goodreau S, Krivitsky P, Morris M, Bojanowski M (2021). statnet.data: Network Datasets for the Statnet Suite. R package version 0.1-0, <URL: https://statnet.org>.
The data set is based upon a model fit to data from one school community from the AddHealth Study, Wave I (Resnick et al., 1997). It was constructed as follows:
A vector representing the sex of each student in the school was randomly re-ordered. The same was done with the students' response to questions on race and grade. These three attribute vectors were permuted independently. Missing values for each were randomly assigned with weights determined by the size of the attribute classes in the school.
The following ergm::ergm()
formula was used to fit a model to the
original data:
~ edges + nodefactor("Grade") + nodefactor("Race") + nodefactor("Sex") + nodematch("Grade",diff=TRUE) + nodematch("Race",diff=TRUE) + nodematch("Sex",diff=FALSE) + gwdegree(1.0,fixed=TRUE) + gwesp(1.0,fixed=TRUE) + gwdsp(1.0,fixed=TRUE)
The resulting model fit was then applied to a network with actors possessing the permuted attributes and with the same number of edges as in the original data.
The processes for handling missing data and defining the race attribute are described in Hunter, Goodreau \& Handcock (2008).
Hunter D.R., Goodreau S.M. and Handcock M.S. (2008). Goodness of Fit of Social Network Models, Journal of the American Statistical Association.
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.
Other undirected networks:
davis
,
ecoli
,
faux.magnolia.high
,
florentine
,
kapferer
,
molecule
,
zach
Other high school networks:
faux.desert.high
,
faux.dixon.high
,
faux.magnolia.high
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