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The ROC region of a regression tree

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  • Jin, Hua
  • Lu, Ying

Abstract

Multiple alternative diagnostic tests for one disease are commonly available to clinicians. It is important to use all the good diagnostic predictors simultaneously to establish a new predictor with higher diagnostic accuracy. The linear combinations of multiple predictors are often of particular interest to clinicians. In this paper, we focused on tree-based nonlinear combinations of multiple predictors. A receiver operating characteristic region and its area under the upper boundary were used to evaluate diagnostic utilities for these algorithms. Some mathematical properties were discussed and non-parametric estimation methods were presented.

Suggested Citation

  • Jin, Hua & Lu, Ying, 2009. "The ROC region of a regression tree," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 936-942, April.
  • Handle: RePEc:eee:stapro:v:79:y:2009:i:7:p:936-942
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    References listed on IDEAS

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    1. Anna N. Angelos Tosteson & Colin B. Begg, 1988. "A General Regression Methodology for ROC Curve Estimation," Medical Decision Making, , vol. 8(3), pages 204-215, August.
    2. Hua Jin & Ying Lu, 2008. "A Procedure for Determining Whether a Simple Combination of Diagnostic Tests May Be Noninferior to the Theoretical Optimum Combination," Medical Decision Making, , vol. 28(6), pages 909-916, November.
    3. Margaret Sullivan Pepe, 2000. "An Interpretation for the ROC Curve and Inference Using GLM Procedures," Biometrics, The International Biometric Society, vol. 56(2), pages 352-359, June.
    4. Gürler, Ülkü & Prewitt, Kathryn, 2000. "Bivariate Density Estimation with Randomly Truncated Data," Journal of Multivariate Analysis, Elsevier, vol. 74(1), pages 88-115, July.
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    Cited by:

    1. Yuxin Zhu & Mei‐Cheng Wang, 2022. "Obtaining optimal cutoff values for tree classifiers using multiple biomarkers," Biometrics, The International Biometric Society, vol. 78(1), pages 128-140, March.
    2. Mei-Cheng Wang & Shanshan Li, 2012. "Bivariate Marker Measurements and ROC Analysis," Biometrics, The International Biometric Society, vol. 68(4), pages 1207-1218, December.

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