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, for example the individual treatment effect),
(3) subgroup identification models (find subsets of patients with similar treatment effects),
and (4) parameter estimation and inference (for the overall population and discovered subgroups).
These tools can directly feed into stratified medicine algorithms including PRISM
(patient response identifiers for stratified medicine; Jemielita and Mehrotra 2019 (in progress)).
PRISM is a flexible and general framework which accepts user-created models/functions. This
package is in beta and will be continually updated.
dplyr, partykit, ranger, survival, glmnet, ggplot2, mvtnorm
knitr, rmarkdown, MASS, zoo, BART, grf, survRM2, TH.data,
coin, rpart

dplyr, partykit, ranger, survival, glmnet, ggplot2, ggparty,
mvtnorm
knitr, rmarkdown, MASS, zoo, BART, grf, survRM2, TH.data,
coin, rpart, testthat (>= 2.1.0)

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, for example the individual treatment effect),
(3) subgroup identification models (find subsets of patients with similar treatment effects),
and (4) parameter estimation and inference (for the overall population and discovered subgroups).
These tools can directly feed into stratified medicine algorithms including PRISM
(patient response identifiers for stratified medicine; Jemielita and Mehrotra (2019)
<arXiv:1912.03337>. PRISM is a flexible and general framework which accepts
user-created models/functions. This package is in beta and will be continually updated.
knitr, rmarkdown, MASS, BART, randomForestSRC, grf, survRM2,
TH.data, coin, rpart, testthat (>= 2.1.0)

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, for example the individual treatment effect),
(3) subgroup identification models (find subsets of patients with similar treatment effects),
and (4) parameter estimation and inference (for the overall population and discovered subgroups).
These tools can directly feed into stratified medicine algorithms including PRISM
(patient response identifiers for stratified medicine; Jemielita and Mehrotra 2019
<arXiv:1912.03337>. PRISM is a flexible and general framework which accepts
user-created models/functions. This package is in beta and will be continually updated.
knitr, rmarkdown, MASS, BART, survRM2, TH.data, coin, rpart,
testthat (>= 2.1.0)