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Presmoothed Landmark estimators of the transition probabilities

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Resumo:Multi-state models can be successfully used to model complicated event history data, for example, describing stages in the disease progression of a patient. In these models one important goal is the estimation of the transition probabilities since they allow for long term prediction of the process. There have been several recent contributions for the estimation of the transition probabilities. Recently, de Uña- Álvarez and Meira-Machado (2015) proposed new estimators for these quantities, and their superiority with respect to the competing estimators has been proved in situations in which the Markov condition is violated. In this paper, we propose a modification of the estimator proposed by de Uña-Álvarez and Meira-Machado based on presmoothing. Simulations show that the presmoothed estimators may be much more efficient than the completely nonparametric estimator.
Autores principais:Machado, Luís Meira
Assunto:Kaplan-Meier Multi-state model Nonparametric estimation Transition probabilities Ciências Naturais::Matemáticas
Ano:2016
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho

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