Package: aVirtualTwins 1.0.1
aVirtualTwins: Adaptation of Virtual Twins Method from Jared Foster
Research of subgroups in random clinical trials with binary outcome and two treatments groups. This is an adaptation of the Jared Foster method (<https://www.ncbi.nlm.nih.gov/pubmed/21815180>).
Authors:
aVirtualTwins_1.0.1.tar.gz
aVirtualTwins_1.0.1.zip(r-4.5)aVirtualTwins_1.0.1.zip(r-4.4)aVirtualTwins_1.0.1.zip(r-4.3)
aVirtualTwins_1.0.1.tgz(r-4.4-any)aVirtualTwins_1.0.1.tgz(r-4.3-any)
aVirtualTwins_1.0.1.tar.gz(r-4.5-noble)aVirtualTwins_1.0.1.tar.gz(r-4.4-noble)
aVirtualTwins_1.0.1.tgz(r-4.4-emscripten)aVirtualTwins_1.0.1.tgz(r-4.3-emscripten)
aVirtualTwins.pdf |aVirtualTwins.html✨
aVirtualTwins/json (API)
# Install 'aVirtualTwins' in R: |
install.packages('aVirtualTwins', repos = c('https://prise6.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/prise6/avirtualtwins/issues
- sepsis - Clinical Trial for Sepsis desease
Last updated 7 years agofrom:e78be83e6e. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 08 2024 |
R-4.5-win | OK | Nov 08 2024 |
R-4.5-linux | OK | Nov 08 2024 |
R-4.4-win | OK | Nov 08 2024 |
R-4.4-mac | OK | Nov 08 2024 |
R-4.3-win | OK | Nov 08 2024 |
R-4.3-mac | OK | Nov 08 2024 |
Exports:formatRCTDatasetvt.dataVT.difftvt.forestVT.forest.doubleVT.forest.foldVT.forest.oneVT.objectvt.subgroupsvt.treeVT.tree.classVT.tree.reg
Dependencies:codetoolscoinlatticelibcoinMASSMatrixmatrixStatsmodeltoolsmultcompmvtnormpartyrandomForestrpartsandwichstrucchangesurvivalTH.datazoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
aVirtualTwins : An adapation of VirtualTwins method created by Jared Foster. | aVirtualTwins-package aVirtualTwins |
RCT format for Virtual Twins | formatRCTDataset |
Clinical Trial for Sepsis desease | sepsis |
Initialize virtual twins data | vt.data |
Difference between twins | VT.difft |
Create forest to compute difft | vt.forest |
Difft by Random Forest | VT.forest |
Difft by double random forest | VT.forest.double |
Difft via k random forests | VT.forest.fold |
Difft by one random forest | VT.forest.one |
VT.object | VT.object |
VT.predict generic function | VT.predict VT.predict,RandomForest,data.frame,character-method VT.predict,randomForest,data.frame,character-method VT.predict,RandomForest,missing,character-method VT.predict,randomForest,missing,character-method VT.predict,train,ANY,character-method VT.predict,train,missing,character-method |
Visualize subgroups | vt.subgroups |
Trees to find Subgroups | vt.tree |
Tree to find subgroup | VT.tree |
Classification tree to find subgroups | VT.tree.class |
Regression tree to find subgroups | VT.tree.reg |