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Clayton copula for survival data with dependent censoring: An application to a tuberculosis treatment adherence data.
Schneider, Silvana; Dos Reis, Rodrigo Citton P; Gottselig, Maicon M F; Fisch, Patrícia; Knauth, Daniela Riva; Vigo, Álvaro.
Afiliación
  • Schneider S; Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
  • Dos Reis RCP; Graduate Program in Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
  • Gottselig MMF; Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
  • Fisch P; Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
  • Knauth DR; Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
  • Vigo Á; Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Stat Med ; 42(23): 4057-4081, 2023 10 15.
Article en En | MEDLINE | ID: mdl-37720988
Ignoring the presence of dependent censoring in data analysis can lead to biased estimates, for example, not considering the effect of abandonment of the tuberculosis treatment may influence inferences about the cure probability. In order to assess the relationship between cure and abandonment outcomes, we propose a copula Bayesian approach. Therefore, the main objective of this work is to introduce a Bayesian survival regression model, capable of taking into account the dependent censoring in the adjustment. So, this proposed approach is based on Clayton's copula, to provide the relation between survival and dependent censoring times. In addition, the Weibull and the piecewise exponential marginal distributions are considered in order to fit the times. A simulation study is carried out to perform comparisons between different scenarios of dependence, different specifications of prior distributions, and comparisons with the maximum likelihood inference. Finally, we apply the proposed approach to a tuberculosis treatment adherence dataset of an HIV cohort from Alvorada-RS, Brazil. Results show that cure and abandonment outcomes are negatively correlated, that is, as long as the chance of abandoning the treatment increases, the chance of tuberculosis cure decreases.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tuberculosis / Cumplimiento y Adherencia al Tratamiento Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: America do sul / Brasil Idioma: En Revista: Stat Med Año: 2023 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tuberculosis / Cumplimiento y Adherencia al Tratamiento Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: America do sul / Brasil Idioma: En Revista: Stat Med Año: 2023 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido