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From the help desk: Comparing areas under receiver operating characteristic curves from two or more probit or logit models

Author

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  • Mario A. Cleves

    (Department of Pediatrics, University of Arkansas for Medical Sciences)

Abstract

Occasionally, there is a need to compare the predictive accuracy of several fitted logit (logistic) or probit models by comparing the areas under the corresponding receiver operating characteristic (ROC) curves. Although Stata currently does not have a ready routine for comparing two or more ROC areas generated from these models, this article describes how these comparisons can be performed using Stata's roccomp command. Copyright 2002 by Stata Corporation.

Suggested Citation

  • Mario A. Cleves, 2002. "From the help desk: Comparing areas under receiver operating characteristic curves from two or more probit or logit models," Stata Journal, StataCorp LP, vol. 2(3), pages 301-313, August.
  • Handle: RePEc:tsj:stataj:v:2:y:2002:i:3:p:301-313
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    Cited by:

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    3. C. Simon Fan & Xiangdong Wei & Junsen Zhang, 2017. "Soft Skills, Hard Skills, And The Black/White Wage Gap," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 1032-1053, April.
    4. Bengtsson, Elias & Grothe, Magdalena & Lepers, Etienne, 2020. "Home, safe home: Cross-country monitoring framework for vulnerabilities in the residential real estate sector," Journal of Banking & Finance, Elsevier, vol. 112(C).
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    6. Ngokkuen, Chuthaporn & Grote, Ulrike, 2012. "Geographical Indication for Jasmine Rice: Applying a Logit Model to Predict Adoption Behavior of Thai Farm Households," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 51(2), pages 1-29, May.
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    9. Cole, Matthew T. & Guillin, Amélie, 2015. "The determinants of trade agreements in services vs. goods," International Economics, Elsevier, vol. 144(C), pages 66-82.
    10. Hernandez Tinoco, Mario & Wilson, Nick, 2013. "Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 394-419.
    11. Simon Cornée, 2012. "The Relevance of Soft Information for Predicting Small Business Credit Default: Evidence from a Social Bank," Economics Working Paper Archive (University of Rennes & University of Caen) 201226, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS, revised Sep 2015.
    12. Gary E. Bolton & David J. Kusterer & Johannes Mans, 2019. "Inflated Reputations: Uncertainty, Leniency, and Moral Wiggle Room in Trader Feedback Systems," Management Science, INFORMS, vol. 65(11), pages 5371-5391, November.
    13. Noraidatulakma Abdullah & Nor Azian Abdul Murad & John Attia & Christopher Oldmeadow & Mohd Arman Kamaruddin & Nazihah Abd Jalal & Norliza Ismail & Rahman Jamal & Rodney J. Scott & Elizabeth G. Hollid, 2018. "Differing Contributions of Classical Risk Factors to Type 2 Diabetes in Multi-Ethnic Malaysian Populations," IJERPH, MDPI, vol. 15(12), pages 1-15, December.

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