Package: networksem 0.4

networksem: Network Structural Equation Modeling

Several methods have been developed to integrate structural equation modeling techniques with network data analysis to examine the relationship between network and non-network data. Both node-based and edge-based information can be extracted from the network data to be used as observed variables in structural equation modeling. To facilitate the application of these methods, model specification can be performed in the familiar syntax of the 'lavaan' package, ensuring ease of use for researchers. Technical details and examples can be found at <https://bigsem.psychstat.org>.

Authors:Zhiyong Zhang [aut, cre], Ziqian Xu [aut]

networksem_0.4.tar.gz
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networksem_0.4.tgz(r-4.6-any)networksem_0.4.tgz(r-4.5-any)
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networksem_0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
networksem/json (API)

# Install 'networksem' in R:

install.packages('networksem', repos = c('https://johnnyzhz.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

friend_data - Friendship network data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 290 downloads 5 exports 90 dependencies

Last updated from:304d7bb1b2. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	128
source / vignettes	OK	183
linux-release	OK	149
macos-release	OK	232
macos-oldrel	OK	211
windows-devel	OK	113
windows-release	OK	117
windows-oldrel	OK	111
wasm-release	OK	132

Exports:path.networksem sem.net sem.net.edge sem.net.edge.lsm sem.net.lsm

Dependencies:abind cachem cli coda codetools cpp11 DEoptimR digest doParallel dotCall64 dplyr edgeR ergm evaluate farver fastmap foreach future future.apply generics ggplot2 globals glue gtable highr hms igraph influential irlba isoband iterators janitor knitr labeling latentnet lattice lavaan lifecycle limma listenv locfit lpSolveAPI lubridate magrittr MASS Matrix memoise mnormt mvtnorm network numDeriv parallelly pbivnorm pillar pkgconfig progressr purrr quadprog R6 ranger rbibutils RColorBrewer Rcpp RcppEigen Rdpack rlang rle robustbase S7 scales SeuratObject sna snakecase sp spam statmod statnet.common stringi stringr tibble tidyr tidyselect timechange trust utf8 vctrs viridisLite withr xfun yaml

Help page	Topics
Friendship network data	friend_data
Calculate a mediation effect from a networksem model	path.networksem
Fit a Structural Equation Model (SEM) with both network and non-network data by incorporating node-level network statistics as variables.	sem.net
Compute user-specified network statistics for a specific network.	sem.net.addvar
Compute a list of user-specified network statistics using the "influential" package and add it to the existing data.	sem.net.addvar.influential
Compute a list of user-specified network statistics values using the "sna" package and add them to the non-network data.	sem.net.addvar.stat
Fit a Structural Equation Model (SEM) with both network and non-network data by transforming nonnetwork data into paired values corresponding to network edge values.	sem.net.edge
Fit a Structural Equation Model (SEM) with both network and non-network data by transforming nonnetwork data into paired values corresponding to network latent distance pairs.	sem.net.edge.lsm
Fit a Structural Equation Model (SEM) with both network and non-network data by incorporating network latent positions as variables.	sem.net.lsm
Summarize output from networksem functions includeing sem.net, sem.net.lsm, sem.net.edge, sem.net.edge.lsm.	summary.networksem

Package: networksem 0.4

networksem: Network Structural Equation Modeling

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)