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Missing data

XW Xuqiang Wei
BL Baoyan Liu
LH Liyun He
XY Xingyue Yang
JZ Jincao Zhou
HZ Hong Zhao
JL Jia Liu
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Although we have internal quality control methods to ensure data integrity, follow-up nonresponse shall be an inescapable challenge in a prospective observation study. Fortunately, we will recruit experienced physicians with stable patient population (at least 5 years of acupuncture experience or middle and senior titles), so the bias for lack of follow-up could be controlled partially. Real-time monitoring of the electronic network platform shall control missing data less than 20%. According to the classical rules of missing classification, follow-up nonresponse belongs to missing not at random (MNAR) [40]. Multiple imputation invented by Rubin shall be adopted to process missing data [41].

Copyright and License information: The Author(s). ©2019
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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