Package: hdmed 1.0.1
Dylan Clark-Boucher
hdmed: Methods for Mediation Analysis with High-Dimensional Mediators
A suite of functions for performing mediation analysis with high-dimensional mediators. In addition to centralizing code from several existing packages for high-dimensional mediation analysis, we provide organized, well-documented functions for a handle of methods which, though programmed their original authors, have not previously been formalized into R packages or been made presentable for public use. The methods we include cover a broad array of approaches and objectives, and are described in detail by both our companion manuscript---"Methods for Mediation Analysis with High-Dimensional DNA Methylation Data: Possible Choices and Comparison"---and the original publications that proposed them. The specific methods offered by our package include the Bayesian sparse linear mixed model (BSLMM) by Song et al. (2019); high-dimensional mediation analysis (HDMA) by Gao et al. (2019); high-dimensional multivariate mediation (HDMM) by Chén et al. (2018); high-dimensional linear mediation analysis (HILMA) by Zhou et al. (2020); high-dimensional mediation analysis (HIMA) by Zhang et al. (2016); latent variable mediation analysis (LVMA) by Derkach et al. (2019); mediation by fixed-effect model (MedFix) by Zhang (2021); pathway LASSO by Zhao & Luo (2022); principal component mediation analysis (PCMA) by Huang & Pan (2016); and sparse principal component mediation analysis (SPCMA) by Zhao et al. (2020). Citations for the corresponding papers can be found in their respective functions.
Authors:
hdmed_1.0.1.tar.gz
hdmed_1.0.1.tar.gz(r-4.5-noble)hdmed_1.0.1.tar.gz(r-4.4-noble)
hdmed_1.0.1.tgz(r-4.4-emscripten)hdmed_1.0.1.tgz(r-4.3-emscripten)
hdmed.pdf |hdmed.html✨
hdmed/json (API)
# Install 'hdmed' in R: |
install.packages('hdmed', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- med_dat - Mediation Example Dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 months agofrom:700c87a559. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 12 2024 |
R-4.5-linux | NOTE | Dec 12 2024 |
Exports:mediate_bslmmmediate_hdmamediate_hdmmmediate_hilmamediate_himamediate_lvmamediate_medfixmediate_pcmamediate_plassomediate_spcma
Dependencies:backportsbamabase64encBHbootbslibcachemcheckmatecliclustercodetoolscolorspacecpp11data.tabledigestevaluatefansifarverfastmapfontawesomeforeachforeignFormulafreebirdfsgcdnetgenlassoggplot2glmnetgluegridExtragtablehdihighrHmischtmlTablehtmltoolshtmlwidgetsigraphisobanditeratorsjquerylibjsonliteknitrlabelinglarslatticelifecyclelinproglme4lpSolvemagrittrMASSMatrixmediationmemoisemgcvmimeminqamunsellmvtnormncvregnlmenloptrnnetpillarpkgconfigR6rappdirsRColorBrewerRcppRcppArmadilloRcppDistRcppEigenrlangrmarkdownRmosekrpartrstudioapisandwichsassscalesscalregshapestringistringrsurvivaltibbletinytexutf8vctrsviridisviridisLitewithrxfunyamlzoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Mediation Example Dataset | med_dat |
Bayesian Sparse Linear Mixed Model | mediate_bslmm |
High-Dimensional Mediation Analysis | mediate_hdma |
High-dimensional Multivariate Mediation Analysis with Principal Directions of Mediation | mediate_hdmm |
High-Dimensional Linear Mediation Analysis | mediate_hilma |
High-Dimensional Mediation Analysis | mediate_hima |
Latent Variable Mediation Analysis | mediate_lvma |
Mediation Analysis via Fixed Effects Model | mediate_medfix |
Principal Component Mediation Analysis for High-dimensional Mediators | mediate_pcma |
Pathway LASSO for Mediation Analysis with High-Dimensional Mediators | mediate_plasso |
Sparse Principal Component Mediation Analysis for High-Dimensional Mediators | mediate_spcma |