Sample Size Calculations for Comparing Groups with Binary Outcomes

Xunan Zhang; Jiangnan Lyu; Justin Tu; Jinyuan Liu; Xiang Lu

doi:10.11919/j.issn.1002-0829.217132

Sample Size Calculations for Comparing Groups with Binary Outcomes

Shanghai Arch Psychiatry. 2017 Oct 25;29(5):316-324. doi: 10.11919/j.issn.1002-0829.217132.

Authors

Xunan Zhang¹, Jiangnan Lyu², Justin Tu³, Jinyuan Liu⁴, Xiang Lu⁵

Affiliations

¹ Department of Statistics, University of California, Berkeley, CA, USA.
² Department of Mathematics, University of California, San Diego, CA, USA.
³ Department of Physical Medicine and Rehabilitation, University of Virginia School of Medicine Charlottesville, VA, USA.
⁴ Department of Family Medicine and Public Health, University of California, San Diego, CA, USA.
⁵ Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA.

Abstract
in English, Chinese

Sample size is a critical parameter for clinical studies. However, to many biomedical and psychosocial investigators, power and sample size analysis seems like a magic trick of statisticians. In this paper, we continue to discuss power and sample size calculations by focusing on binary outcomes. We again emphasize the importance of close interactions between investigators and biostatisticians in setting up hypotheses and carrying out power analyses.

样本大小是临床研究的一个重要参数。然而，把握度和样本量分析对许多生物医学和社会心理调查者来说似乎是一个统计学家的魔术。在本文中，我们继续讨论二分类结果的把握度和样本量的计算。我们再次强调了在建立假设和进行把握度分析中调查者和生物统计学家之间密切联系的重要性。.

Keywords: binary outcomes; sample size.

Abstract in English, Chinese

Abstract
in English, Chinese