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

Project Title Distributed Regression Analysis Application in Large Distributed Data Networks: Analysis of Precision and Operational Performance
Date
Monday, April 6, 2020
Location
Description

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.

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 

Authors

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

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