HLSM_data: HLSM: Included Data Sets
In HLSM: Hierarchical Latent Space Network Model
Description
Usage
Format
Author(s)
References
Description
Data set included with the HLSM package: network variables from Pitts
and Spillane (2009).
Usage
1
2
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5
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9
10
11
Format
ps.advice.mat: a list of 15 sociomatrices of advice seeking network, one for each school.
ps.advice.df: a data frame of all ties.
ps.all.vars.mat: a list of 15 arrays of all the covariates, one for each school.
edge.vars.mat: a list of edge level covariates for 15 different school.
ps.edge.df: a dataframe of all edge covariates.
ps.school.vars.mat: a list of school level covariates for all 15 schools.
ps.teacher.vars.mat: a list of node level covariates for all 15 schools.
ps.node.df: a dataframe of all node covariates.
ps.all.vars.mat: a single list of length 15 containing the covariates mentioned above.
School9Network: a single adjacency matrix from School 9.
School9NodeCov: a dataframe with node covariates
School9EdgeCov: a dataframe with dyad-level covariates.
Author(s)
Sam Adhikari
References
Pitts, V., & Spillane, J. (2009). "Using social network methods to study school leadership".International Journal of Research & Method in Education, 32, 185-207
Sweet, T.M., Thomas, A.C., and Junker, B.W. (2012).
"Hierarchical Network Models for Education Research: Hierarchical Latent Space Models". Journal of Educational and Behavorial Statistics.
HLSM documentation built on Dec. 11, 2021, 9:43 a.m.
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Description Usage Format Author(s) References
Description
Data set included with the HLSM package: network variables from Pitts and Spillane (2009).
Usage
1 2 3 4 5 6 7 8 9 10 11 |
Format
ps.advice.mat: a list of 15 sociomatrices of advice seeking network, one for each school.
ps.advice.df: a data frame of all ties.
ps.all.vars.mat: a list of 15 arrays of all the covariates, one for each school. edge.vars.mat: a list of edge level covariates for 15 different school.
ps.edge.df: a dataframe of all edge covariates.
ps.school.vars.mat: a list of school level covariates for all 15 schools.
ps.teacher.vars.mat: a list of node level covariates for all 15 schools.
ps.node.df: a dataframe of all node covariates.
ps.all.vars.mat: a single list of length 15 containing the covariates mentioned above.
School9Network: a single adjacency matrix from School 9.
School9NodeCov: a dataframe with node covariates
School9EdgeCov: a dataframe with dyad-level covariates.
Author(s)
Sam Adhikari
References
Pitts, V., & Spillane, J. (2009). "Using social network methods to study school leadership".International Journal of Research & Method in Education, 32, 185-207
Sweet, T.M., Thomas, A.C., and Junker, B.W. (2012). "Hierarchical Network Models for Education Research: Hierarchical Latent Space Models". Journal of Educational and Behavorial Statistics.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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