Distributed Regression Analysis Application in Large Distributed Data Networks: Analysis of Precision and Operational Performance

Basic Details
Monday, April 6, 2020

A distributed data network approach combined with distributed regression analysis (DRA) can reduce the risk of disclosing sensitive individual and institutional information in multicenter studies. However, software that facilitates large-scale and efficient implementation of DRA is limited. This study aimed to assess the precision and operational performance of a DRA application comprising a SAS-based DRA package and a file transfer workflow developed within the open-source distributed networking software PopMedNet in a horizontally partitioned distributed data network.


Qoua Her, Jessica Malenfant, Zilu Zhang, Yury Vilk, Jessica Young, David Tabano, Jack Hamilton, Ron Johnson, Marsha Raebel, Denise Boudreau, Sengwee Toh

Corresponding Author

Qoua Her, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States

Email: qouaher@gmail.com