Nonparametric estimation of transition probabilities in a non-Markov illness-death model.
In this paper we consider nonparametric estimation of transition probabilities for multi-state models. Specifically, we focus on the illness-death or disability model. The main novelty of the proposed estimators is that they do not rely on the Markov assumption, typically assumed to hold in a multi-state model. We investigate the asymptotic properties of the introduced estimators, such as their consistency and their convergence to a normal law. Simulations demonstrate that the new estimators may outperform Aalen-Johansen estimators (the classical nonparametric tool for estimating the transition probabilities) in non-Markov situation. An illustration through real data analysis is included.
Meira-Machado
Luís
L
Department of Mathematics for Science and Technology, University of Minho, Guimaraes, Portugal. lmachado@mct.uminho.pt
de Uña-Alvarez
Jacobo
J
Cadarso-Suárez
Carmen
C
D000319:Adrenergic beta-Antagonists / Q000627:therapeutic use; D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D003718:Denmark; D006470:Hemorrhage / Q000139:chemically induced; D006801:Humans; D008103:Liver Cirrhosis / Q000628:therapy; D008954:Models, Biological; D015233:Models, Statistical; D011433:Propranolol / Q000627:therapeutic use; D015911:Sclerotherapy; D018709:Statistics, Nonparametric; D016019:Survival Analysis
D000319:Adrenergic beta-Antagonists; D011433:Propranolol