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A Note on the Effect of Data Clustering on the Multiple-Imputation Variance Estimator: A Theoretical Addendum to the Lewis et al. article in JOS 2014 Cover

A Note on the Effect of Data Clustering on the Multiple-Imputation Variance Estimator: A Theoretical Addendum to the Lewis et al. article in JOS 2014

Journal of Official Statistics
Volume 32 (2016): Issue 1 (March 2016)
By: Yulei He,  Iris Shimizu,  Susan Schappert,  Jianmin Xu,  Vladislav Beresovsky,  Diba Khan,  Roberto Valverde and  Nathaniel Schenker  
Open Access
|Mar 2016

Authors

Yulei He

wdq7@cdc.gov

Iris Shimizu

ims1@cdc.gov

Susan Schappert

sds0@cdc.gov

Jianmin Xu

ewl4@cdc.gov

Vladislav Beresovsky

hvy4@cdc.gov

Diba Khan

ild1@cdc.gov

Roberto Valverde

rcv4@cdc.gov

Nathaniel Schenker

nhs1@cdc.gov

DOI: https://doi.org/10.1515/jos-2016-0007 | Journal eISSN: 2001-7367
Journal RSS Feed
Language: English
Page range: 147 - 164
Submitted on: Oct 1, 2014
|
Accepted on: Jun 1, 2015
|
Published on: Mar 10, 2016
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Bayesian,
complex survey design,
data release,
exploratory data analysis,
fraction of missing information,
missing data
Related subjects:
Mathematics,
Probability and statistics

© 2016 Yulei He, Iris Shimizu, Susan Schappert, Jianmin Xu, Vladislav Beresovsky, Diba Khan, Roberto Valverde, Nathaniel Schenker, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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