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Non-and Semi-Parametric Estimation of Transition Probabilities from Censored Observation of a Non-Homogeneous Markov Process

Per Kragh Andersen, Lars Sommer Hansen and Niels Keiding
Scandinavian Journal of Statistics
Vol. 18, No. 2 (1991), pp. 153-167
Stable URL: http://www.jstor.org/stable/4616198
Page Count: 15
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Non-and Semi-Parametric Estimation of Transition Probabilities from Censored Observation of a Non-Homogeneous Markov Process
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Abstract

Non-homogeneous Markov process models for life history data are studied. We review Aalen & Johansen's (1978) methodology for estimating transition probabilities in such models and extend the methods to the case where each transition intensity is specified via a proportional intensities regression model. Data from a clinical trial in liver cirrhosis serve as illustration.

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