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Semiparametric and parametric transformation models for comparing diagnostic markers with paired design

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  • Kelly Zou
  • W. J. Hall

Abstract

We develop semiparametric and parametric transformation models for estimation and comparison of ROC curves derived from measurements from two diagnostic tests on the same subjects. We assume the existence of transformed measurement scales, one for each test, on which the paired measurements have bivariate normal distributions. The resulting pair of ROC curves are estimated by maximum likelihood algorithms, using joint rank data in the semiparametric model with unspecified transformations and using Box-Cox transformations in the parametric transformation case. Several hypothesis tests for comparing the two ROC curves, or characteristics of them, are developed. Two clinical examples are presented and simulation results are provided.

Suggested Citation

  • Kelly Zou & W. J. Hall, 2002. "Semiparametric and parametric transformation models for comparing diagnostic markers with paired design," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(6), pages 803-816.
    • Handle: RePEc:taf:japsta:v:29:y:2002:i:6:p:803-816
    DOI: 10.1080/02664760220136140
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    References listed on IDEAS

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    1. Kelly Zou & W. J. Hall, 2000. "Two transformation models for estimating an ROC curve derived from continuous data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(5), pages 621-631.
    2. E. S. Venkatraman, 2000. "A Permutation Test to Compare Receiver Operating Characteristic Curves," Biometrics, The International Biometric Society, vol. 56(4), pages 1134-1138, December.
    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.
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    Cited by:

    1. Yu, Wenbao & Park, Taesung, 2015. "Two simple algorithms on linear combination of multiple biomarkers to maximize partial area under the ROC curve," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 15-27.
    2. Kelly Zou & W. J. Hall, 2002. "On estimating a transformation correlation coefficient," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(5), pages 745-760.

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