Towards a better understanding of correlation

J. C. Rayner; Eric J. Beh

doi:10.1111/j.1467-9574.2009.00425.x

Towards a better understanding of correlation

J. C. Rayner, Eric J. Beh

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20 Citations (Scopus)

Abstract

Correlation is often used to assess both independence and linearity in two dimensions, but is not well understood in higher dimensions. Here we take a closer look at these uses of correlation in two dimensions and how these assessments might be extended to higher dimensions. Our discussion will focus on the simple case of understanding the nature of correlation for association models for two- and three-way contingency tables, but can also be considered in a more general setting.

Original language	English
Pages (from-to)	324-333
Number of pages	10
Journal	Statistica Neerlandica
Volume	63
Issue number	3
DOIs	https://doi.org/10.1111/j.1467-9574.2009.00425.x
Publication status	Published - 2009

Keywords

components
correlation analysis
geometric linearity
mathematical models
polynomials
structural linearity

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10.1111/j.1467-9574.2009.00425.x

Cite this

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abstract = "Correlation is often used to assess both independence and linearity in two dimensions, but is not well understood in higher dimensions. Here we take a closer look at these uses of correlation in two dimensions and how these assessments might be extended to higher dimensions. Our discussion will focus on the simple case of understanding the nature of correlation for association models for two- and three-way contingency tables, but can also be considered in a more general setting.",

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AB - Correlation is often used to assess both independence and linearity in two dimensions, but is not well understood in higher dimensions. Here we take a closer look at these uses of correlation in two dimensions and how these assessments might be extended to higher dimensions. Our discussion will focus on the simple case of understanding the nature of correlation for association models for two- and three-way contingency tables, but can also be considered in a more general setting.

KW - components

KW - correlation analysis

KW - geometric linearity

KW - mathematical models

KW - polynomials

KW - structural linearity

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DO - 10.1111/j.1467-9574.2009.00425.x

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JO - Statistica Neerlandica

JF - Statistica Neerlandica

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Towards a better understanding of correlation

Abstract

Keywords

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