CRAN/E | pda

pda

Privacy-Preserving Distributed Algorithms

Installation

About

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 () for safe and convenient collaboration. For more information, please visit our software websites: , and .

Key Metrics

Version 1.2.7
R ≥ 4.1.0
Published 2024-03-04 60 days ago
Needs compilation? yes
License Apache License 2.0
CRAN checks pda results

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Maintainer

Maintainer

Jiajie Chen

jiajie.chen@pennmedicine.upenn.edu

Authors

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

lab / cph

(PennCIL)

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

pda archive

Depends

R ≥ 4.1.0

Imports

Rcpp ≥ 0.12.19
stats
httr
rvest
jsonlite
data.table
survival
minqa
glmnet
MASS
numDeriv
metafor
ordinal
plyr

Suggests

imager
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LinkingTo

Rcpp
RcppArmadillo