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Bewick, Viv, Liz Cheek, and Jonathan Ball. “Statistics review 13: receiver operating characteristic curves.” Critical care 8.6 (2004): 508.

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Article

Receiver Operating Characteristic (ROC) Curve Analysis: A Tutorial Using Body Mass Index (BMI) as a Measure of Obesity

1Health Promotion Program, Montana State University - Northern, & Health Demographics, Havre, MT 59501, USA


Journal of Physical Activity Research. 2016, Vol. 1 No. 1, 5-8
DOI: 10.12691/jpar-1-1-2
Copyright © 2015 Science and Education Publishing

Cite this paper:
Peter D. Hart. Receiver Operating Characteristic (ROC) Curve Analysis: A Tutorial Using Body Mass Index (BMI) as a Measure of Obesity. Journal of Physical Activity Research. 2016; 1(1):5-8. doi: 10.12691/jpar-1-1-2.

Correspondence to: Peter  D. Hart, Health Promotion Program, Montana State University - Northern, & Health Demographics, Havre, MT 59501, USA. Email: peter.hart@msun.edu

Abstract

The purpose of this tutorial-based lecture is to show the usefulness of performing a receiver operating characteristic (ROC) curve analysis. The lecture will explain the background terminology associated with a ROC curve analysis, show the necessary SAS software coding to run a ROC curve analysis, and finally help interpret the analysis output in order to make informed research decisions. An example evaluating body mass index (BMI) cutoff scores indicating obesity is used in the tutorial.

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