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The American Statistician Volume 70, 2016 - Issue 4
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STATISTICAL PRACTICE

Bias Introduced by Rounding in Multiple Imputation for Ordered Categorical Variables

Yan XiaDepartment of Educational Psychology and Learning Systems, College of Education, Florida State University, Tallahassee, FL, USA
&
Yanyun YangDepartment of Educational Psychology and Learning Systems, College of Education, Florida State University, Tallahassee, FL, USA
Pages 358-364 | Received 01 Nov 2014, Published online: 21 Nov 2016

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Wesley S. McCann. (2022) Assessing equifinality in Islamic extremist pathways using fsQCA. Dynamics of Asymmetric Conflict 15:3, pages 224-254.
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Irene Epifanio, M. Victoria Ibáñez & Amelia Simó. (2020) Archetypal Analysis With Missing Data: See All Samples by Looking at a Few Based on Extreme Profiles. The American Statistician 74:2, pages 169-183.
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Articles from other publishers (2)

Zachary K. Collier, Minji Kong, Olushola Soyoye, Kamal Chawla, Ann M. Aviles & Yasser Payne. (2023) Deep Learning Imputation for Asymmetric and Incomplete Likert-Type Items. Journal of Educational and Behavioral Statistics.
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Tanayott Thaweethai, David E. Arterburn, Karen J. Coleman & Sebastien Haneuse. (2021) Robust inference when combining inverse-probability weighting and multiple imputation to address missing data with application to an electronic health records-based study of bariatric surgery. The Annals of Applied Statistics 15:1.
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