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Identifiability of Models for Multiple Diagnostic Testing in the Absence of a Gold Standard

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  • Geoffrey Jones
  • Wesley O. Johnson
  • Timothy E. Hanson
  • Ronald Christensen

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  • Geoffrey Jones & Wesley O. Johnson & Timothy E. Hanson & Ronald Christensen, 2010. "Identifiability of Models for Multiple Diagnostic Testing in the Absence of a Gold Standard," Biometrics, The International Biometric Society, vol. 66(3), pages 855-863, September.
    • Handle: RePEc:bla:biomet:v:66:y:2010:i:3:p:855-863
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01330.x
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    References listed on IDEAS

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    1. Bruce D. Spencer, 2007. "Estimating the Accuracy of Jury Verdicts," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 4(2), pages 305-329, July.
    2. Nandini Dendukuri & Elham Rahme & Patrick Bélisle & Lawrence Joseph, 2004. "Bayesian Sample Size Determination for Prevalence and Diagnostic Test Studies in the Absence of a Gold Standard Test," Biometrics, The International Biometric Society, vol. 60(2), pages 388-397, June.
    3. Nandini Dendukuri & Lawrence Joseph, 2001. "Bayesian Approaches to Modeling the Conditional Dependence Between Multiple Diagnostic Tests," Biometrics, The International Biometric Society, vol. 57(1), pages 158-167, March.
    4. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    5. Paul S. Albert & Lori E. Dodd, 2004. "A Cautionary Note on the Robustness of Latent Class Models for Estimating Diagnostic Error without a Gold Standard," Biometrics, The International Biometric Society, vol. 60(2), pages 427-435, June.
    6. Marios P. Georgiadis & Wesley O. Johnson & Ian A. Gardner & Ramanpreet Singh, 2003. "Correlation‐adjusted estimation of sensitivity and specificity of two diagnostic tests," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(1), pages 63-76, January.
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    Cited by:

    1. Leandro García Barrado & Els Coart & Tomasz Burzykowski, 2017. "Estimation of diagnostic accuracy of a combination of continuous biomarkers allowing for conditional dependence between the biomarkers and the imperfect reference-test," Biometrics, The International Biometric Society, vol. 73(2), pages 646-655, June.
    2. Huiping Xu & Xiaochun Li & Zuoyi Zhang & Shaun Grannis, 2022. "Score test for assessing the conditional dependence in latent class models and its application to record linkage," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1663-1687, November.
    3. Hanson, Timothy E. & de Carvalho, Miguel & Chen, Yuhui, 2017. "Bernstein polynomial angular densities of multivariate extreme value distributions," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 60-66.
    4. Geoffrey Jones & Wesley O. Johnson, 2016. "A Bayesian Superpopulation Approach to Inference for Finite Populations Based on Imperfect Diagnostic Outcomes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(2), pages 314-327, June.
    5. G. Jones & W. O. Johnson & W. D. Vink & N. French, 2012. "A Framework for the Joint Modeling of Longitudinal Diagnostic Outcome Data and Latent Infection Status: Application to Investigating the Temporal Relationship between Infection and Disease," Biometrics, The International Biometric Society, vol. 68(2), pages 371-379, June.
    6. Wang, Zheyu & Sebestyen, Krisztian & Monsell, Sarah E., 2017. "Model-based clustering for assessing the prognostic value of imaging biomarkers and mixed type tests," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 125-135.
    7. Christopher S. McMahan & Joshua M. Tebbs & Timothy E. Hanson & Christopher R. Bilder, 2017. "Bayesian regression for group testing data," Biometrics, The International Biometric Society, vol. 73(4), pages 1443-1452, December.

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