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Correlation and Simple Linear Regression

Radiology · 2003 · Vol. 227(3) · pp. 617–628
Kelly H. ZouKemal TuncaliStuart G. Silverman

Abstract

In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

Statistical Methods and InferenceLiver Disease Diagnosis and TreatmentAdvanced Causal Inference TechniquesSimple linear regressionLinear regressionMedicineCorrelationStatisticsPearson product-moment correlation coefficientSpearman's rank correlation coefficientRegression analysisStandardized coefficientCorrelation coefficient

MeSH terms

Factor Analysis, StatisticalFluoroscopyHumansRadiation DosageTomography, X-Ray ComputedRadiology, InterventionalLinear ModelsStatistics, Nonparametric
Citations
1,069
FWCI
9.99
field-weighted impact
References
34
Percentile
99%
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References
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