The Division of Biostatistics at the Department of Preventive Medicine invites you to attend the following seminar.
Presenter: Dr. Sixia Chen (University of Oklahoma Health Sciences Center)
Title: “Nonparametric Mass Imputation for Data Integration”
Abstract: Data integration combining a probability sample with another non-probability sample is an emerging area of research in survey sampling. We consider the case when the study variable of interest is measured only in the non-probability sample, but comparable auxiliary information is available for both data sources. We consider mass imputation for the probability sample using the non-probability data as the training set for imputation. The parametric mass imputation is sensitive to parametric model assumptions. To develop improved and robust methods, we consider nonparametric mass imputation for data integration. In particular, we consider kernel smoothing for a low-dimensional covariate and generalized additive models for a relatively high-dimensional covariate for imputation. Asymptotic theories and variance estimation are developed. Simulation studies and real applications show the benefits of our proposed methods over parametric counterparts.
Presenter’s website: https://sites.google.com/view/schen0713/%E9%A6%96%E9%A1%B5
ZOOM Virtual Room Connection:
Join from PC, Mac, Linux, iOS or Android: https://tennessee.zoom.us/j/99322680124
Or iPhone one-tap (US Toll): +16468769923,99322680124# or +13017158592,99322680124#
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Meeting ID: 993 2268 0124
International numbers available: https://tennessee.zoom.us/u/abNgxz4Vyw
NOTE: The host will moderate questions. Questions can be typed in the chat box at any time during the seminar, and the host will ask them or invite seminar attenders to ask others at the end of the seminar.
We look forward to seeing you all among us.
Chi-Yang Chiu, Ph.D.
Assistant Professor of Biostatistics
Department of Preventive Medicine, UTHSC