학술논문
DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models
Document Type
article
Author
Chongliang Luo; Md. Nazmul Islam; Natalie E. Sheils; John Buresh; Jenna Reps; Martijn J. Schuemie; Patrick B. Ryan; Mackenzie Edmondson; Rui Duan; Jiayi Tong; Arielle Marks-Anglin; Jiang Bian; Zhaoyi Chen; Talita Duarte-Salles; Sergio Fernández-Bertolín; Thomas Falconer; Chungsoo Kim; Rae Woong Park; Stephen R. Pfohl; Nigam H. Shah; Andrew E. Williams; Hua Xu; Yujia Zhou; Ebbing Lautenbach; Jalpa A. Doshi; Rachel M. Werner; David A. Asch; Yong Chen
Source
Nature Communications, Vol 13, Iss 1, Pp 1-10 (2022)
Subject
Language
English
ISSN
2041-1723
Abstract
A lossless, one-shot and privacy-preserving distributed algorithm was revealed for fitting linear mixed models on multi-site data. The algorithm was applied to a study of 120,609 COVID-19 patients using only minimal aggregated data from each of 14 sites.