pda: Privacy-Preserving Distributed Algorithms

A collection of privacy-preserving distributed algorithms for conducting multi-site data analyses. The regression analyses can be linear regression for continuous outcome, logistic regression for binary outcome, Cox proportional hazard regression for time-to event outcome, Poisson regression for count outcome, or multi-categorical regression for nominal or ordinal outcome. The PDA algorithm runs on a lead site and only requires summary statistics from collaborating sites, with one or few iterations. The package can be used together with the online system (<https://pda-ota.pdamethods.org/>) for safe and convenient collaboration. For more information, please visit our software websites: <https://github.com/Penncil/pda>, and <https://pdamethods.org/>.

Version: 1.2.6
Depends: R (≥ 4.1.0)
Imports: Rcpp (≥ 0.12.19), stats, httr, rvest, jsonlite, data.table, survival, minqa, glmnet, MASS, numDeriv, metafor, ordinal, plyr
LinkingTo: Rcpp, RcppArmadillo
Suggests: imager, lme4
Published: 2023-03-08
Author: Chongliang Luo [aut], Rui Duan [aut], Mackenzie Edmondson [aut], Jiayi Tong [aut], Xiaokang Liu [aut], Kenneth Locke [aut], Jiajie Chen [cre], Yong Chen [aut], Penn Computing Inference Learning (PennCIL) lab [cph]
Maintainer: Jiajie Chen <jiajie.chen at pennmedicine.upenn.edu>
License: Apache License 2.0
NeedsCompilation: yes
Materials: NEWS
CRAN checks: pda results

Documentation:

Reference manual: pda.pdf

Downloads:

Package source: pda_1.2.6.tar.gz
Windows binaries: r-devel: pda_1.2.6.zip, r-release: pda_1.2.6.zip, r-oldrel: pda_1.2.6.zip
macOS binaries: r-release (arm64): pda_1.2.6.tgz, r-oldrel (arm64): pda_1.2.6.tgz, r-release (x86_64): pda_1.2.6.tgz
Old sources: pda archive

Linking:

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