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Maximum likelihood estimation of parameters of signal detection theory—A direct solution

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  • Donald Dorfman
  • Edward Alf

Abstract

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Suggested Citation

  • Donald Dorfman & Edward Alf, 1968. "Maximum likelihood estimation of parameters of signal detection theory—A direct solution," Psychometrika, Springer;The Psychometric Society, vol. 33(1), pages 117-124, March.
    • Handle: RePEc:spr:psycho:v:33:y:1968:i:1:p:117-124
    DOI: 10.1007/BF02289677
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    Cited by:

    1. Sean F. Reardon & Andrew D. Ho, 2015. "Practical Issues in Estimating Achievement Gaps From Coarsened Data," Journal of Educational and Behavioral Statistics, , vol. 40(2), pages 158-189, April.
    2. Juana-María Vivo & Manuel Franco & Donatella Vicari, 2018. "Rethinking an ROC partial area index for evaluating the classification performance at a high specificity range," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(3), pages 683-704, September.
    3. Cheam, Amay S.M. & McNicholas, Paul D., 2016. "Modelling receiver operating characteristic curves using Gaussian mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 192-208.
    4. Maria G.M. Hunink & Douglas K. Richardson & Peter M. Doubilet & Colin B. Begg, 1990. "Testing for Fetal Pulmonary Maturity," Medical Decision Making, , vol. 10(3), pages 201-211, August.
    5. Lloyd, Chris J. & Yong, Zhou, 1999. "Kernel estimators of the ROC curve are better than empirical," Statistics & Probability Letters, Elsevier, vol. 44(3), pages 221-228, September.
    6. Robert M. Centor, 1985. "A Visicalc Program for Estimating the Area Under a Receiver Operating Characteristic (ROC) Curve," Medical Decision Making, , vol. 5(2), pages 139-148, June.
    7. Chris J. Lloyd, 2000. "Regression Models for Convex ROC Curves," Biometrics, The International Biometric Society, vol. 56(3), pages 862-867, September.
    8. Zhongkai Liu & Howard D. Bondell, 2019. "Binormal Precision–Recall Curves for Optimal Classification of Imbalanced Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(1), pages 141-161, April.
    9. Jean Mary Zarate & Caroline R Ritson & David Poeppel, 2013. "The Effect of Instrumental Timbre on Interval Discrimination," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-9, September.
    10. Laurens Beran, 2014. "Hypothesis tests to determine if all true positives have been identified on a receiver operating characteristic curve," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1332-1341, June.

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