Publicação
Estimation of the conditional survival function with interval-censored data
| Resumo: | This paper focuses on the estimation of the conditional survival function in the presence of interval-censored data. While estimation is relatively straightforward for qualitative covariates using Turnbull’s estimator, the case of continuous covariates, particularly under interval censoring, poses additional methodological challenges. We describe existing kernel-based approaches, such as those using Nadaraya-Watson weights, applicable under right censoring. The main contribution of this work is the proposal of two novel methodologies tailored for estimating the conditional survival function when data are interval-censored. These methods use kernel weights and a modified EM algorithm to provide practical ways to solve this challenging problem. |
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| Autores principais: | Machado, Luís Meira |
| Assunto: | Survival analysis Interval censoring Conditional survival function Nonparametric estimation |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | This paper focuses on the estimation of the conditional survival function in the presence of interval-censored data. While estimation is relatively straightforward for qualitative covariates using Turnbull’s estimator, the case of continuous covariates, particularly under interval censoring, poses additional methodological challenges. We describe existing kernel-based approaches, such as those using Nadaraya-Watson weights, applicable under right censoring. The main contribution of this work is the proposal of two novel methodologies tailored for estimating the conditional survival function when data are interval-censored. These methods use kernel weights and a modified EM algorithm to provide practical ways to solve this challenging problem. |
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