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DOI: 10.1148/radiol.2273011499
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(Radiology 2003;227:617-628.)
© RSNA, 2003


Statistical Concepts Series

Correlation and Simple Linear Regression1

Kelly H. Zou, PhD, Kemal Tuncali, MD and Stuart G. Silverman, MD

1 From the Department of Radiology, Brigham and Women’s Hospital (K.H.Z., K.T., S.G.S.) and Department of Health Care Policy (K.H.Z.), Harvard Medical School, 180 Longwood Ave, Boston, MA 02115. Received September 10, 2001; revision requested October 31; revision received December 26; accepted January 21, 2002. Address correspondence to K.H.Z. (e-mail: zou@bwh.harvard.edu).

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.

© RSNA, 2003

Index terms: Data analysis • Statistical analysis




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