Common pitfalls in statistical analysis: Measures of agreement

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...

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Main Authors:	Priya Ranganathan, C S Pramesh, Rakesh Aggarwal
Format:	Article
Language:	English
Published:	Wolters Kluwer Medknow Publications 2017-01-01
Series:	Perspectives in Clinical Research
Subjects:	Agreement biostatistics concordance
Online Access:	http://www.picronline.org/article.asp?issn=2229-3485;year=2017;volume=8;issue=4;spage=187;epage=191;aulast=Ranganathan

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spelling	doaj-c39d12007dbf409c8e17896e277b05f92020-11-24T21:47:20ZengWolters Kluwer Medknow PublicationsPerspectives in Clinical Research2229-34852017-01-018418719110.4103/picr.PICR_123_17Common pitfalls in statistical analysis: Measures of agreementPriya RanganathanC S PrameshRakesh AggarwalAgreement 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.http://www.picronline.org/article.asp?issn=2229-3485;year=2017;volume=8;issue=4;spage=187;epage=191;aulast=RanganathanAgreementbiostatisticsconcordance
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Priya Ranganathan C S Pramesh Rakesh Aggarwal
spellingShingle	Priya Ranganathan C S Pramesh Rakesh Aggarwal Common pitfalls in statistical analysis: Measures of agreement Perspectives in Clinical Research Agreement biostatistics concordance
author_facet	Priya Ranganathan C S Pramesh Rakesh Aggarwal
author_sort	Priya Ranganathan
title	Common pitfalls in statistical analysis: Measures of agreement
title_short	Common pitfalls in statistical analysis: Measures of agreement
title_full	Common pitfalls in statistical analysis: Measures of agreement
title_fullStr	Common pitfalls in statistical analysis: Measures of agreement
title_full_unstemmed	Common pitfalls in statistical analysis: Measures of agreement
title_sort	common pitfalls in statistical analysis: measures of agreement
publisher	Wolters Kluwer Medknow Publications
series	Perspectives in Clinical Research
issn	2229-3485
publishDate	2017-01-01
description	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.
topic	Agreement biostatistics concordance
url	http://www.picronline.org/article.asp?issn=2229-3485;year=2017;volume=8;issue=4;spage=187;epage=191;aulast=Ranganathan
work_keys_str_mv	AT priyaranganathan commonpitfallsinstatisticalanalysismeasuresofagreement AT cspramesh commonpitfallsinstatisticalanalysismeasuresofagreement AT rakeshaggarwal commonpitfallsinstatisticalanalysismeasuresofagreement
_version_	1725897709614792704

Common pitfalls in statistical analysis: Measures of agreement

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