Implements linear, logistic, and Cox regression on vertically partitioned data across several data partners. Data is not shared between data partners or the analysis center and the computations can be considered secure. Three different protocols are implemented. 2-Party: two data partners which communicate directly without an intermediate analysis center; 2T-Party: two data partners communicate indirectly via an analysis center, and KT-Party: two or more data partners plus an analysis center are all allowed to communicate directly. 2-Party and 2^T-Party use a form of secure multiplication as found in Karr, et. al. (2009) "Privacy-Preserving Analysis of Vertically Partitioned Data Using Secure Matrix Products" and Slavkovic et. al. (2007) "Secure Logistic Regression of Horizontally and Vertically Partitioned Distributed Databases" <doi:10.1109/ICDMW.2007.114>. Full details can be found in Samizo (In preparation).
|Depends:||R (≥ 3.6.0)|
|Suggests:||survival (≥ 3.2-7), knitr (≥ 1.28), rmarkdown (≥ 2.2)|
|Author:||Thomas Kent [aut, cre], Yuji Samizo [aut]|
|Maintainer:||Thomas Kent <kentedegrees at gmail.com>|
|CRAN checks:||vdra results|
An Introduction to the VDRA Package
How to Use the VDRA Package with PopMedNet
VDRA Communications and Files
|Windows binaries:||r-devel: vdra_1.0.0.zip, r-release: vdra_1.0.0.zip, r-oldrel: vdra_1.0.0.zip|
|macOS binaries:||r-release (arm64): vdra_1.0.0.tgz, r-oldrel (arm64): vdra_1.0.0.tgz, r-release (x86_64): vdra_1.0.0.tgz, r-oldrel (x86_64): vdra_1.0.0.tgz|
Please use the canonical form https://CRAN.R-project.org/package=vdra to link to this page.