Privacy-Preserving Distributed Algorithms
ADAP derivatives
ADAP surrogate estimation
ADAP initialize
dGEM hospital-specific effect derivation
dGEM standardized event rate estimation
dGEM initialize
PDA dGEM synthesize
PDA DLM estimation
DLM initialize
DPQL derive
PDA DPQL estimation
DPQL initialize
gather cloud settings into a list
A flexible version of MASS::glmmPQL
Generate pda UWZ derivatives
Generate pda UWZ summary statistics before calculating derivatives
PDA surrogate estimation
ODAC initialize
PDA synthesize surrogate estimates from all sites, optional
ODACAT derivatives
PDA surrogate estimation
ODACAT initialize
PDA synthesize surrogate estimates from all sites, optional
ODACATH derivatives
PDA surrogate estimation
ODACATH initialize
PDA synthesize surrogate estimates from all sites, optional
ODAH derivatives
PDA surrogate estimation
ODAH initialize
ODAL derivatives
PDA surrogate estimation
ODAL initialize
PDA synthesize surrogate estimates from all sites, optional
ODAP derivatives
PDA surrogate estimation
ODAP initialize
ODAPB derivatives
PDA surrogate estimation
ODAPB initialize
PDA: Privacy-preserving Distributed Algorithm
Function to download json and return as object
Function to list available objects
Function to upload object to cloud as json
pda control synchronize
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/>.