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统计分析中的常见陷阱：一致性度量

Common pitfalls in statistical analysis: Measures of agreement.

作者信息

Ranganathan Priya, Pramesh C S, Aggarwal Rakesh

机构信息

Department of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India.

Department of Surgical Oncology, Tata Memorial Centre, Mumbai, Maharashtra, India.

出版信息

Perspect Clin Res. 2017 Oct-Dec;8(4):187-191. doi: 10.4103/picr.PICR_123_17.

DOI:10.4103/picr.PICR_123_17
PMID:29109937
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5654219/
Abstract

Agreement between measurements refers to the degree of concordance between two (or more) sets of measurements. Statistical methods to test agreement are used to assess inter-rater variability or to decide whether one technique for measuring a variable can substitute another. In this article, we look at statistical measures of agreement for different types of data and discuss the differences between these and those for assessing correlation.

摘要

测量之间的一致性是指两组（或多组）测量结果之间的一致程度。用于检验一致性的统计方法用于评估评分者间的变异性，或确定一种测量变量的技术是否可以替代另一种。在本文中，我们将探讨不同类型数据的一致性统计量度，并讨论这些量度与评估相关性的量度之间的差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f118/5654219/d50c7d65f15b/PCR-8-187-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f118/5654219/09ec2497b14c/PCR-8-187-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f118/5654219/d50c7d65f15b/PCR-8-187-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f118/5654219/09ec2497b14c/PCR-8-187-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f118/5654219/d50c7d65f15b/PCR-8-187-g005.jpg

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