aVirtualTwins

An adaptation of VirtualTwins method from Foster, J. C., Taylor, J. M.G. and Ruberg, S. J. (2011)

VirtualTwins is a method of subgroup identification from randomized clinical trial data.

As an intern in a french pharmaceutical group, i worked on this method and develop a package based on Jared Foster and al method.

(Very) Quick Preview

# Load data
data(sepsis)
# Format data
vt.obj <- vt.data(sepsis, "survival", "THERAPY", T)
# First step : create random forest model
vt.for <- vt.forest("one", vt.obj, T, ntree = 500)
# Second step : find rules in data 
vt.trees <- vt.tree("class", vt.for, threshold = quantile(vt.for$difft, seq(.5,.8,.1)), maxdepth = 2)
# Print results
vt.sbgrps <- vt.subgroups(vt.trees)
knitr::kable(vt.sbgrps)

	Subgroup	Subgroup size	Treatement event rate	Control event rate	Treatment sample size	Control sample size	RR (resub)	RR (snd)
tree1	PRAPACHE>=26.5	157	0.752	0.327	105	52	2.300	1.856
tree3	PRAPACHE>=26.5 & AGE>=51.74	120	0.897	0.31	78	42	2.894	1.991

## Infos

Currently this package works for RCT with two treatments groups and binary outcome.

This is the dev version 0.0.0.2 and often updated.

Most of the package use Reference Class programing (in R). Feel free to create your own classes.

I got a WARNING when Checking package for "cheking PDF version of manual" because of my version of LaTeX. Need to fix it.

To-do list

• Description and help
• Vignette example
• ...

Install

# use devtools library
library(devtools)
# install from github
devtools::install_github("prise6/aVirtualTwins@dev")
# load library
library(aVirtualTwins)

Help

• Vignette is really not finished ...

See full-example

or when installed :

vignette("full-example", package = "aVirtualTwins")