pda: Privacy-Preserving Distributed Algorithms (original) (raw)
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: | 1.2.7 |
|---|---|
| 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: | 2024-03-04 |
| DOI: | 10.32614/CRAN.package.pda |
| 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:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=pdato link to this page.