Publicação
Conditional estimation of the bivariate distribution under dependent right censoring
| Resumo: | In many medical studies individuals can experience several events across a follow-up study. In these studies, the times between two consecutive events are often of interest and lead to problems that have received much at- tention. Most of the times, one will be interested in describing the distribution of the joint gap times, the marginal distribution of the gap times but also the correlation structure among them. In recent years significant contributions have been made regarding this topic. However, most approaches assume independent censoring and do not account for the influence of covariates. This manuscript introduces two estimators that account for dependent censoring while including covariate information. A real data illustration is included. |
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| Autores principais: | Moreira, Ana Cristina |
| Outros Autores: | Machado, Luís Meira |
| Assunto: | Beran estimator Bivariate distribution Conditional survival Dependent censoring Kaplan-Meier |
| Ano: | 2012 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | In many medical studies individuals can experience several events across a follow-up study. In these studies, the times between two consecutive events are often of interest and lead to problems that have received much at- tention. Most of the times, one will be interested in describing the distribution of the joint gap times, the marginal distribution of the gap times but also the correlation structure among them. In recent years significant contributions have been made regarding this topic. However, most approaches assume independent censoring and do not account for the influence of covariates. This manuscript introduces two estimators that account for dependent censoring while including covariate information. A real data illustration is included. |
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