Package: regmed 2.1.5

regmed: Regularized Mediation Analysis

Mediation analysis for multiple mediators by penalized structural equation models with different types of penalties depending on whether there are multiple mediators and only one exposure and one outcome variable (using sparse group lasso) or multiple exposures, multiple mediators, and multiple outcome variables (using lasso, L1, penalties).

Authors:Jason Sinnwell [aut, cre], Daniel Schaid [aut]

regmed_2.1.5.tar.gz
regmed_2.1.5.zip(r-4.7-x86_64)regmed_2.1.5.zip(r-4.7-arm64)regmed_2.1.5.zip(r-4.6-x86_64)regmed_2.1.5.zip(r-4.6-arm64)regmed_2.1.5.zip(r-4.5-x86_64)
regmed_2.1.5.tgz(r-4.6-x86_64)regmed_2.1.5.tgz(r-4.6-arm64)regmed_2.1.5.tgz(r-4.5-x86_64)regmed_2.1.5.tgz(r-4.5-arm64)
regmed_2.1.5.tar.gz(r-4.7-arm64)regmed_2.1.5.tar.gz(r-4.7-x86_64)regmed_2.1.5.tar.gz(r-4.6-arm64)regmed_2.1.5.tar.gz(r-4.6-x86_64)
regmed_2.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
regmed/json (API)

# Install 'regmed' in R:

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

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

med - Simulated dataset for regmed package
x - Simulated dataset for regmed package
y - Simulated dataset for regmed package

On CRAN:

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

openblas cpp

3.00 score 2 stars 8 scripts 287 downloads 23 exports 26 dependencies

Last updated from:97a1753b05. Checks:15 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	132
linux-devel-x86_64	OK	194
source / vignettes	OK	256
linux-release-arm64	OK	124
linux-release-x86_64	OK	147
macos-release-arm64	OK	153
macos-release-x86_64	OK	255
macos-oldrel-arm64	OK	158
macos-oldrel-x86_64	OK	276
windows-devel-arm64	OK	448
windows-devel-x86_64	OK	183
windows-release-arm64	OK	424
windows-release-x86_64	OK	140
windows-oldrel-x86_64	OK	126
wasm-release	OK	133

Exports:mvregmed.edges mvregmed.fit mvregmed.grid mvregmed.grid.bestfit mvregmed.lavaan.dat mvregmed.lavaan.model plot.mvregmed.edges plot.mvregmed.grid plot.regmed.edges plot.regmed.grid print.regmed print.regmed.grid regmed.edges regmed.fit regmed.grid regmed.grid.bestfit regmed.lavaan.dat regmed.lavaan.model regmed.prefilter summary.lavaan summary.mvregmed summary.mvregmed.grid summary.regmed

Dependencies:cli cpp11 evaluate glasso glue gtools highr igraph knitr lattice lavaan lifecycle magrittr MASS Matrix mnormt numDeriv pbivnorm pkgconfig quadprog Rcpp RcppArmadillo rlang vctrs xfun yaml

Regularized_Mediation_Examples

Overview | Simulated dataset | regmed: Mediation model for 1 exposure, multiple mediators, and 1 outcome variable | Pre-filter mediators | Grid of lambda penalties | Fit regmed for grid of lambda penalties | Select best model from grid by minimum BIC | Fit single regmed model with user-specified lambda | Plot directed graph of fit model | Lavaan sem: Estimate parameters of selected model without imposing penalty | mvregmed : Mediation model for multiple exposures, multiple mediators, and multiple outcome variables | Fit mvregmed for a grid for lambda penalties | Select best model from grid based on minimum BIC | Fit single mvregmed model with user-specified lambda | Lavaan sem: Estimate parameters of seleted model without imposing penalty | Interpretation of lavaan output | References

Rendered fromregmed.Rmdusingknitr::rmarkdown

Last update: 2023-01-20
Started: 2021-04-12

Citation

Readme and manuals

Help Manual

Help page	Topics
Regularized Mediation Analysis	regmed-package regmed
Simulated dataset for regmed package	med medsim x y
Helper function to check x, y, mediator for input to mvregmed functions	mvregmed.dat.check regmed.dat.check
For an object of class mvregmed, create edges for a graph object that can be used for plots, or for creating models input to lavaan function sem	mvregmed.edges plot.mvregmed.edges
Multivariate regularized mediation model	mvregmed.fit
Setup attributes of graph object for plotting	mvregmed.graph.attributes
Fit a grid of mvregmed models over a vector of lambda penalty parameters	mvregmed.grid summary.mvregmed.grid
Choose best fit model from a grid search based on minimum Bayesian Information Criterion	mvregmed.grid.bestfit
Helper function to summarize fits of models across a grid of lambda values	mvregmed.grid.data
Helper function to update parameters in a grid search	mvregmed.grid.update
Helper function to setup data and parameters for input to mvregmed.fit and mvregmed.grid	mvregmed.init
Set up data to input to lavaan sem	mvregmed.lavaan.dat
Setup a model for input to lavaan	mvregmed.lavaan.model
Plot penalty parameter lambda versus BIC for model fits	plot.mvregmed.grid
Plots for regmed.grid object.	plot.regmed.grid
For an object of class regmed, create edges for a graph object that can be used for plots, or for creating models input to lavaan function sem	plot.regmed.edges regmed.edges
Regularized Mediation model for a specified lambda penalty value.	print.regmed regmed.fit summary.regmed
Regularized mediation models over a vector grid of lambda penalty values.	print.regmed.grid regmed.grid summary.regmed.grid
Find best fitting regmed model from regmed.grid object.	regmed.grid.bestfit
Set up data to input to lavaan sem	regmed.lavaan.dat
Create a lavaan model	regmed.lavaan.model summary.lavaan
Prefilter to reduce the number of mediators for subsequent analyses	regmed.prefilter
Summary of mvregmed object	summary.mvregmed

Package: regmed 2.1.5

regmed: Regularized Mediation Analysis

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)