2012The Journal of PhysiologyOpen access

Categorized or continuous? Strength of an association – and linear regression

Gordon B. Drummond, Sarah L. Vowler

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Abstract

Key points Correlation and regression are used with continuous variables Plot the variables in correlation and regression relationships to aid interpretation An association between two discrete measurements is assessed by correlation Regression describes and quantifies a relationship between an independent factor and a dependent variable; prediction is also possible Few biological relationships are truly linear Regression can be distorted by outlying values Absence of a linear regression does not mean a relationship is not present Regression is very frequently misused and mis‐applied

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Key points Correlation and regression are used with continuous variables Plot the variables in correlation and regression relationships to aid interpretation An association between two discrete measurements is assessed by correlation Regression describes and quantifies a relationship between an independent factor and a dependent variable; prediction is also possible Few biological relationships are truly linear Regression can be distorted by outlying values Absence of a linear regression does not mean a relationship is not present Regression is very frequently misused and mis‐applied

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Available abstract

Key points Correlation and regression are used with continuous variables Plot the variables in correlation and regression relationships to aid interpretation An association between two discrete measurements is assessed by correlation Regression describes and quantifies a relationship between an independent factor and a dependent variable; prediction is also possible Few biological relationships are truly linear Regression can be distorted by outlying values Absence of a linear regression does not mean a relationship is not present Regression is very frequently misused and mis‐applied

Key concepts: Linear regression, Proper linear model, Statistics, Regression analysis, Regression, Regression diagnostic, Segmented regression, Linear predictor function

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