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Schneider S, Dos Reis RCP, Gottselig MMF, Fisch P, Knauth DR, Vigo Á. Clayton copula for survival data with dependent censoring: An application to a tuberculosis treatment adherence data. Stat Med 2023; 42:4057-4081. [PMID: 37720988 DOI: 10.1002/sim.9858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 06/30/2023] [Accepted: 07/10/2023] [Indexed: 09/19/2023]
Abstract
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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Affiliation(s)
- Silvana Schneider
- Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Graduate Program in Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Rodrigo Citton P Dos Reis
- Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Maicon M F Gottselig
- Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Patrícia Fisch
- Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Epidemiology Department, Hospital Nossa Senhora da Conceição, Porto Alegre, Rio Grande do Sul, Brazil
| | - Daniela Riva Knauth
- Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Álvaro Vigo
- Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
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Lin YH, Sun LH, Tseng YJ, Emura T. The Pareto type I joint frailty-copula model for clustered bivariate survival data. COMMUN STAT-SIMUL C 2022. [DOI: 10.1080/03610918.2022.2066694] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Yuan-Hsin Lin
- Graduate Institute of Statistics, National Central University, Taoyuan City, Taiwan
- Department of Information Management, National Central University, Taoyuan City, Taiwan
| | - Li-Hsien Sun
- Graduate Institute of Statistics, National Central University, Taoyuan City, Taiwan
| | - Yi-Ju Tseng
- Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Takeshi Emura
- Biostatistics Center, Kurume University, Kurume, Japan
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A Meta-Analysis for Simultaneously Estimating Individual Means with Shrinkage, Isotonic Regression and Pretests. AXIOMS 2021. [DOI: 10.3390/axioms10040267] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Meta-analyses combine the estimators of individual means to estimate the common mean of a population. However, the common mean could be undefined or uninformative in some scenarios where individual means are “ordered” or “sparse”. Hence, assessments of individual means become relevant, rather than the common mean. In this article, we propose simultaneous estimation of individual means using the James–Stein shrinkage estimators, which improve upon individual studies’ estimators. We also propose isotonic regression estimators for ordered means, and pretest estimators for sparse means. We provide theoretical explanations and simulation results demonstrating the superiority of the proposed estimators over the individual studies’ estimators. The proposed methods are illustrated by two datasets: one comes from gastric cancer patients and the other from COVID-19 patients.
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Assessing the numerical integration of dynamic prediction formulas using the exact expressions under the joint frailty-copula model. JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE 2021. [DOI: 10.1007/s42081-021-00133-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance. JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE 2021. [DOI: 10.1007/s42081-021-00124-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
AbstractThe dynamics of the wild boar population has become a pressing issue not only for ecological purposes, but also for agricultural and livestock production. The data related to the wild boar dispersal distance can have a complex structure, including excess of zeros and right-censored observations, thus being challenging for modeling. In this sense, we propose two different zero-inflated-right-censored regression models, assuming Weibull and gamma distributions. First, we present the construction of the likelihood function, and then, we apply both models to simulated datasets, demonstrating that both regression models behave well. The simulation results point to the consistency and asymptotic unbiasedness of the developed methods. Afterwards, we adjusted both models to a simulated dataset of wild boar dispersal, including excess of zeros, right-censored observations, and two covariates: age and sex. We showed that the models were useful to extract inferences about the wild boar dispersal, correctly describing the data mimicking a situation where males disperse more than females, and age has a positive effect on the dispersal of the wild boars. These results are useful to overcome some limitations regarding inferences in zero-inflated-right-censored datasets, especially concerning the wild boar’s population. Users will be provided with an R function to run the proposed models.
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Likelihood analysis and stochastic EM algorithm for left truncated right censored data and associated model selection from the Lehmann family of life distributions. JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE 2021. [DOI: 10.1007/s42081-021-00115-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Huang XW, Wang W, Emura T. A copula-based Markov chain model for serially dependent event times with a dependent terminal event. JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE 2020. [DOI: 10.1007/s42081-020-00087-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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