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Artigo de periodico
Bayesian estimation for performance measures of two diagnostic tests in the presence of verification bias (2010)
Aragon, Davi Casale; Martinez, Edson Zangiacomi; Achcar, Jorge Alberto
Source: Journal of Biopharmaceutical Statistics. Unidades: FMRP, ICMC
Subjects: DIAGNÓSTICO (TESTES), INFERÊNCIA BAYESIANA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ARAGON, Davi Casale e MARTINEZ, Edson Zangiacomi e ACHCAR, Jorge Alberto. Bayesian estimation for performance measures of two diagnostic tests in the presence of verification bias. Journal of Biopharmaceutical Statistics, v. 20, n. 4, p. 821-834, 2010Tradução . . Acesso em: 02 nov. 2024.
APA
Aragon, D. C., Martinez, E. Z., & Achcar, J. A. (2010). Bayesian estimation for performance measures of two diagnostic tests in the presence of verification bias. Journal of Biopharmaceutical Statistics, 20( 4), 821-834.
NLM
Aragon DC, Martinez EZ, Achcar JA. Bayesian estimation for performance measures of two diagnostic tests in the presence of verification bias. Journal of Biopharmaceutical Statistics. 2010 ; 20( 4): 821-834.[citado 2024 nov. 02 ]
Vancouver
Aragon DC, Martinez EZ, Achcar JA. Bayesian estimation for performance measures of two diagnostic tests in the presence of verification bias. Journal of Biopharmaceutical Statistics. 2010 ; 20( 4): 821-834.[citado 2024 nov. 02 ]
Artigo de periodico
Estimators of sensitivity and specificity in the presence of verification bias: a Bayesian approach (2006)
Martinez, Edson Zangiacomi; Achcar, Jorge Alberto ; Louzada, Francisco
Source: Computational Statistics & Data Analysis. Unidades: FMRP, ICMC
Subjects: INFERÊNCIA BAYESIANA, DIAGNÓSTICO (TESTES)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINEZ, Edson Zangiacomi e ACHCAR, Jorge Alberto e LOUZADA, Francisco. Estimators of sensitivity and specificity in the presence of verification bias: a Bayesian approach. Computational Statistics & Data Analysis, v. 51, p. 601-611, 2006Tradução . . Disponível em: https://doi.org/10.1016/j.csda.2005.12.021. Acesso em: 02 nov. 2024.
APA
Martinez, E. Z., Achcar, J. A., & Louzada, F. (2006). Estimators of sensitivity and specificity in the presence of verification bias: a Bayesian approach. Computational Statistics & Data Analysis, 51, 601-611. doi:10.1016/j.csda.2005.12.021
NLM
Martinez EZ, Achcar JA, Louzada F. Estimators of sensitivity and specificity in the presence of verification bias: a Bayesian approach [Internet]. Computational Statistics & Data Analysis. 2006 ; 51 601-611.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1016/j.csda.2005.12.021
Vancouver
Martinez EZ, Achcar JA, Louzada F. Estimators of sensitivity and specificity in the presence of verification bias: a Bayesian approach [Internet]. Computational Statistics & Data Analysis. 2006 ; 51 601-611.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1016/j.csda.2005.12.021
Relatorio tecnico
Bayesian model for semi-latent data with covariates: estimating the performance of diagnosis tests (2005)
Martinez, Edson Zangiacomi; Achcar, Jorge Alberto ; Louzada, Francisco
Unidades: FMRP, ICMC
Subjects: DIAGNÓSTICO (TESTES), INFERÊNCIA BAYESIANA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINEZ, Edson Zangiacomi e ACHCAR, Jorge Alberto e LOUZADA, Francisco. Bayesian model for semi-latent data with covariates: estimating the performance of diagnosis tests. . Ribeirão Preto: FMRP/USP. . Acesso em: 02 nov. 2024. , 2005
APA
Martinez, E. Z., Achcar, J. A., & Louzada, F. (2005). Bayesian model for semi-latent data with covariates: estimating the performance of diagnosis tests. Ribeirão Preto: FMRP/USP.
NLM
Martinez EZ, Achcar JA, Louzada F. Bayesian model for semi-latent data with covariates: estimating the performance of diagnosis tests. 2005 ;[citado 2024 nov. 02 ]
Vancouver
Martinez EZ, Achcar JA, Louzada F. Bayesian model for semi-latent data with covariates: estimating the performance of diagnosis tests. 2005 ;[citado 2024 nov. 02 ]

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