Disparity of Imputed Data from Small Area Estimate Approaches – A Case Study on Diabetes Prevalence at the County Level in the U.S. Cover

Disparity of Imputed Data from Small Area Estimate Approaches – A Case Study on Diabetes Prevalence at the County Level in the U.S.

Data Science Journal

Volume 17 (2018): Issue 0

By: Lung-Chang Chien, Ge Lin, Xiao Li and Xingyou Zhang

Open Access

|Apr 2018

Authors

Lung-Chang Chien

lung-chang.chien@unlv.edu

University of Nevada, Las Vegas

Ge Lin

ge.kan@unlv.edu

University of Nevada, Las Vegas

Xiao Li

Xiao.Li.1@uth.tmc.edu

University of Texas Health Science Center at Houston (UTHealth) School of Public Health

Xingyou Zhang

Xingyou.zhang@census.gov

U.S. Census Bureau

DOI: https://doi.org/10.5334/dsj-2018-008 | Journal eISSN: 1683-1470

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Language: English

Submitted on: Nov 27, 2017

|

Accepted on: Mar 9, 2018

|

Published on: Apr 6, 2018

Published by: Ubiquity Press

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

Small area estimate,

diabetes prevalence,

multi-level logistic regression,

spatial logistic regression,

spatial Poisson regression

© 2018 Lung-Chang Chien, Ge Lin, Xiao Li, Xingyou Zhang, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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