Common Atoms Product Partition Model on Covariates for Generating Synthetic Controls in Single Arm Clinical Trials
Noirrit Kiran Chandra 2023-06-12
An implementation of the CA-PPMx model proposed by (Chandra et al. 2023; Müller, Chandra, and Sarkar 2023). Please cite our works.
The package has been tried and tested in Ubuntu
and macOS
.
libgsl
openmp
R (>= 4.2.2)
devtools::install_github("noirritchandra/CAPPMx", build_vignettes = TRUE)
Must set build_vignettes = TRUE
to install the vignette
files
containing illustrations.
library(CAPPMx)
Check the vignette
files of the package for the reference manual:
vignette("Intro_to_CAPPMx","CAPPMx")
A resampled version of the Glioblastoma dataset used by Chandra et al.
(2023) is included in the CAPPMx
package which can be accessed using
the following:
data("MDACC_reproduced")
head(MDACC_reproduced)
## Surgery Reason Histologic Grade EOR Gender ATRX MGMT CT SOC RT Dose KPS Age
## 1 1 1 1 1 NA 0 0 1 NA 0 0
## 2 1 1 0 0 1 0 0 1 1 0 1
## 3 1 1 0 1 NA 0 0 1 0 0 1
## 4 1 1 1 1 1 0 1 1 1 0 0
## 5 1 1 1 1 1 0 1 1 1 0 0
## 6 1 1 0 1 NA 0 1 1 1 0 1
## endpts surv_inds
## 1 30.71429 FALSE
## 2 78.00000 FALSE
## 3 10.56548 TRUE
## 4 64.70833 FALSE
## 5 44.85119 FALSE
## 6 47.42857 FALSE
Chandra, N. K., A. Sarkar, J de Groot, Y. Yuan, and P. and Müller. 2023. “Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Controls in Clinical Trials.” arXiv Preprint arXiv:2201.00068.
Müller, P., N. K. Chandra, and A. Sarkar. 2023. “Bayesian Approaches to Include Real-World Data in Clinical Studies.” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 381: 20220158.