Package: StratifiedMedicine 1.0.5

StratifiedMedicine: Stratified Medicine

A toolkit for stratified medicine, subgroup identification, and precision medicine. Current tools include (1) filtering models (reduce covariate space), (2) patient-level estimate models (counterfactual patient-level quantities, such as the conditional average treatment effect), (3) subgroup identification models (find subsets of patients with similar treatment effects), and (4) treatment effect estimation and inference (for the overall population and discovered subgroups). These tools can be customized and are directly used in PRISM (patient response identifiers for stratified medicine; Jemielita and Mehrotra 2019 <arxiv:1912.03337>. This package is in beta and will be continually updated.

Authors:Thomas Jemielita [aut, cre]

StratifiedMedicine_1.0.5.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
StratifiedMedicine/json (API)

# Install 'StratifiedMedicine' in R:
install.packages('StratifiedMedicine', repos = c('https://thomasjemielita.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/thomasjemielita/stratifiedmedicine/issues

On CRAN:

Conda:

5.39 score 4 stars 62 scripts 443 downloads 11 exports 54 dependencies

Last updated from:d2e4cfd709. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develWARNING175
source / vignettesOK244
linux-releaseWARNING164
macos-releaseWARNING159
macos-oldrelWARNING126
windows-develWARNING112
windows-releaseWARNING89
windows-oldrelWARNING122
wasm-releaseOK99

Exports:filter_traingenerate_subgrp_dataparam_combineparam_estple_trainplot_dependenceplot_importanceplot_pleplot_treePRISMsubmod_train

Dependencies:backportscheckmateclicodetoolscoincpp11dplyrfarverforeachFormulagenericsggpartyggplot2glmnetgluegtableinumisobanditeratorslabelinglatticelibcoinlifecyclemagrittrMASSMatrixmatrixStatsmodeltoolsmultcompmvtnormpartykitpillarpkgconfigR6rangerRColorBrewerRcppRcppEigenrlangrpartS7sandwichscalesshapestrucchangesurvivalTH.datatibbletidyselectutf8vctrsviridisLitewithrzoo

An Introduction to StratifiedMedicine
Introduction | Filter Models | Patient-level Estimate (PLE) Models | Subgroup Models | Treatment Effect Estimation | PRISM: Patient Response Identifiers for Stratified Medicine | Example: Continuous Outcome with Binary Treatment | Example: Binary Outcome with Binary Treatment | Example: Survival Outcome with Binary Treatment | Resampling | Conclusion
Rendered fromSM_PRISM.Rmdusingknitr::rmarkdown

Last update: 2022-04-03
Started: 2019-06-18

User Specific Models
Filter Model (filter) | Patient-Level Estimates ("ple_train") | Subgroup Identification ("submod_train") | Parameter Estimation ("param_est") | Putting it All Together | Conclusion
Rendered fromSM_User_Models.Rmdusingknitr::rmarkdown

Last update: 2022-04-03
Started: 2019-10-09