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用于比较具有连续结果的组的样本量计算。

Sample Size Calculations for Comparing Groups with Continuous Outcomes.

作者信息

Zheng Julia Z, Li Yangyi, Lin Tuo, Estrada Angelica, Lu Xiang, Feng Changyong

机构信息

Department of Immunology and Microbiology, McGill University, Montreal, Canada.

Department of Mathematics, State University of New York in Stony Brook, Stony Brook, NY, USA.

出版信息

Shanghai Arch Psychiatry. 2017 Aug 25;29(4):250-256. doi: 10.11919/j.issn.1002-0829.217101.

DOI:10.11919/j.issn.1002-0829.217101
PMID:28955148
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5609001/
Abstract

Sample size justification is required for all clinical studies. However, to many biomedical and clinical researchers, power and sample size analysis seems like a magic trick of statisticians. In this note, we discuss power and sample size calculations and show that biomedical and clinical investigators play a significant role in making such analyses possible and meaningful. Thus, power analysis is really an interactive process and scientific researchers and statisticians are equal partners in the research enterprise.

摘要

所有临床研究都需要进行样本量合理性论证。然而,对于许多生物医学和临床研究人员来说,效能和样本量分析似乎是统计学家的一个魔术。在本笔记中,我们讨论效能和样本量计算,并表明生物医学和临床研究人员在使此类分析成为可能且有意义方面发挥着重要作用。因此,效能分析实际上是一个互动过程,科研人员和统计学家在研究事业中是平等的伙伴。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c09/5609001/eca18cec5aa7/sap-29-250-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c09/5609001/fceffda069ed/sap-29-250-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c09/5609001/0163c2b71532/sap-29-250-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c09/5609001/eca18cec5aa7/sap-29-250-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c09/5609001/fceffda069ed/sap-29-250-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c09/5609001/0163c2b71532/sap-29-250-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c09/5609001/eca18cec5aa7/sap-29-250-g003.jpg

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