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Colloquium: A Hierarchical Bayesian Method for Combining Surveys

Event Type: 
Colloquium
Speaker: 
Dr. Yang Cheng
Event Date: 
Tuesday, November 17, 2020 -
3:30pm to 4:30pm
Location: 
Zoom Meetings: https://unm.zoom.us/j/93699560753
Audience: 
General PublicFaculty/StaffStudentsAlumni/Friends

Event Description: 

Title: A Hierarchical Bayesian Method for Combining Surveys

Abstract: In order to estimate the number of occupied households, US Census Bureau conducts many surveys. As a result, we get different estimates of the number of occupied households from these surveys. While each survey is useful, differences among the estimates they produce are sometimes very large. To resolve these differences, we propose in this study a hierarchical Bayesian method to obtain a more reliable estimate of the number occupied households by combining estimates from these surveys. Exploiting the repetitive nature of the surveys, we propose a time series model. We apply our method to the estimates from Current Population Survey (CPS)/Annual Social and Economic Supplement, CPS/Housing Vacancy Survey, American Community Survey, and American Housing Survey between 2002 and 2011 to produce a more reliable estimate of the number of occupied households. We implement our objective Bayesian method by Gibbs sampling.

About the speaker: Dr. Yang Cheng is a senior mathematical statistician at the Research and Development Division (RDD), National Agricultural Statistics Service (NASS). He is also an Adjunct Professor of Statistics in the George Washington University. Earlier, Dr. Yang was a senior mathematical statistician at the Center for Behavioral Health Statistics and Quality (CBHSQ), Substance Abuse and Mental Health Service Administration (SAMHSA). From 2006 to 2019, he served as a Lead Scientist for the Current Population Survey (CPS), American Time Use Survey (ATUS), and Housing Vacancy Survey (HVS) at the U.S. Census Bureau. He also served as a Branch Chief for the Current Population Survey in the Demographic Statistical Methods Division (DSMD) and Program Research Branch in the Governments Division (GOVS). Dr. Yang received a Doctor's degree in Mathematical Statistics from the University of Maryland at College Park. His research interests include statistical modeling, survey methodology, small area estimation, statistical modeling, and labor force statistics.

 

Event Contact

Contact Name: Guoyi Zhang

Contact Email: gzhang@unm.edu