摘要翻译：
新冠肺炎疫情已经并将继续对计划中和正在进行的临床试验产生重大影响。它对试验数据的影响产生了多种潜在的统计问题。影响的规模是史无前例的，但从个别角度来看，许多问题是明确界定和可行的。提出了一些战略和建议，以评估和解决与统计资料、数据缺失、统计分析方法的有效性和修改、补充分析的必要性、实现目标的能力和总体审判的可解释性有关的问题。
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英文标题：
《Statistical Issues and Recommendations for Clinical Trials Conducted
  During the COVID-19 Pandemic》
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作者：
R. Daniel Meyer, Bohdana Ratitch, Marcel Wolbers, Olga Marchenko, Hui
  Quan, Daniel Li, Chrissie Fletcher, Xin Li, David Wright, Yue Shentu, Stefan
  Englert, Wei Shen, Jyotirmoy Dey, Thomas Liu, Ming Zhou, Norman Bohidar,
  Peng-Liang Zhao, Michael Hale
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最新提交年份：
2020
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  The COVID-19 pandemic has had and continues to have major impacts on planned and ongoing clinical trials. Its effects on trial data create multiple potential statistical issues. The scale of impact is unprecedented, but when viewed individually, many of the issues are well defined and feasible to address. A number of strategies and recommendations are put forward to assess and address issues related to estimands, missing data, validity and modifications of statistical analysis methods, need for additional analyses, ability to meet objectives and overall trial interpretability.
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PDF链接：
https://arxiv.org/pdf/2005.10248