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ABSTRACT Nonparametric Estimation of Event Probabilities for Non-Markov Multistate Event Data David Glidden, Department of Biostatistics, University of California-San Francisco Multistate event data, in which a single subject is at risk for multiple
events, is common in biomedical applications. I
consider nonparametric estimation of the vector of probabilities of state
membership at time t. Estimators, which
Aalen and Johansen (1978) derived under the Markov assumption, are shown to
be consistent and asymptotically
Gaussian for data which is non-Markov. In addition, procedures for
confidence bands are
derived in this general setting. The method is evaluated via simulation and
applied to data from two clinical trials.
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