Biostatistics Seminar Series

## Statistical Matching for Data Fusion - Saumyadipta Pyne, University of Pittsburgh

Thursday 4/4 3:30PM - 4:30PM

Public Health Lecture Hall (A115)

Public Health Lecture Hall (A115)

**Statistical Matching for Data Fusion of Complex Phenotypes**

The statistical matching problem involves data fusion with structured missing data. In a canonical version of the problem, there are two datasets A and B, and three sets of variables X, Y, and Z. Dataset A contains observations on the (X, Y) variables, and dataset B contains observations on the (X, Z) variables. A common goal in the statistical matching problem is to impute the missing values in each dataset in order to synthesize a dataset with all the variables (X, Y, Z). We use model-based statistical matching for fusion of complex phenotypes by extending to high-dimensional non-Gaussian data.

Last Updated On Tuesday, April 2, 2019 by Tang, Lu

Created On Monday, January 7, 2019