Data integration with oracle use of external summary information from heterogeneous populations
Online in Zoom
Online in Zoom


The Department of Biostatistics presents a seminar with Dr. Paisong Han. Data integration with oracle use of external summary information from heterogeneous populations.

It is common to have access to summary information from external studies. Such information can be useful in model building for an internal study of interest and can improve parameter estimation efficiency when incorporated. However, external studies may target populations different from the internal study, in which case an incorporation of the corresponding summary
information may introduce estimation bias. We develop a method that selects the external studies whose target population is the same as the internal study and simultaneously incorporates their available information into estimation. The resulting estimator has the efficiency as if we knew which external studies target the same population and made use of information
from those studies alone. The method is applied to a prostate cancer study to incorporate external summary information to improve parameter estimation.

Data integration with oracle use of external summary information from heterogeneous populations

The Department of Biostatistics presents a seminar with Dr. Paisong Han

February 25, 2021
3:30 pm - 5:00 pm
Online in Zoom
Online URL: https://umich.zoom.us/j/97097348674
Contact Information: Amanda Larson, larsoama@umich.edu


The Department of Biostatistics presents a seminar with Dr. Paisong Han. Data integration with oracle use of external summary information from heterogeneous populations.

It is common to have access to summary information from external studies. Such information can be useful in model building for an internal study of interest and can improve parameter estimation efficiency when incorporated. However, external studies may target populations different from the internal study, in which case an incorporation of the corresponding summary
information may introduce estimation bias. We develop a method that selects the external studies whose target population is the same as the internal study and simultaneously incorporates their available information into estimation. The resulting estimator has the efficiency as if we knew which external studies target the same population and made use of information
from those studies alone. The method is applied to a prostate cancer study to incorporate external summary information to improve parameter estimation.