Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/39117

TítuloNonparametric estimation of the survival function for ordered multivariate failure time data: a comparative study
Autor(es)Machado, Luís Meira
Sestelo, Marta
Gonçalves, Andreia
Palavras-chaveSurvival analysis
Survival function
Conditional survival
Gap times
Nonparametric estimation
Recurrent events
EditoraJohn Wiley and Sons
RevistaBiometrical Journal
Resumo(s)In longitudinal studies of disease, patients may experience several events through a follow-up period. In these studies, the sequentially ordered events are often of interest and lead to problems that have received much attention recently. Issues of interest include the estimation of bivariate survival, marginal distributions and the conditional distribution of gap times. In this work we consider the estimation of the survival function conditional to a previous event. Different nonparametric approaches will be considered for estimating these quantities, all based on the Kaplan-Meier estimator of the survival function. We explore the finite sample behavior of the estimators through simulations. The different methods proposed in this article are applied to a data set from a German Breast Cancer Study. The methods are used to obtain predictors for the conditional survival probabilities as well as to study the influence of recurrence in overall survival.
Versão da editoraThe original publication is available at http://onlinelibrary.wiley.com/doi/10.1002/bimj.201500038/abstract
Arbitragem científicayes
Aparece nas coleções:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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