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Nonparametric estimation

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Abstract

We consider n individuals under study with individual multistate processes \((x-^{i}{t}) _{t\geq O,} X^{i} _{t} \epsilon {0,1,2,...,J} , i = 1,2,...n\) We assume that the n processes are, conditional on the initial states X(i) 0 , independent replicates of a multistate process as in Section 8.1. Observation of the individual multistate data is subject to a right-censoring time Ci and possibly also to a left-truncation time Li. We assume that right-censoring and left-truncation are independent as explained in Section 2.2.2.

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Correspondence to Jan Beyersmann .

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© 2012 Springer Science+Business Media, LLC

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Beyersmann, J., Schumacher, M., Allignol, A. (2012). Nonparametric estimation. In: Competing Risks and Multistate Models with R. Use R!. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2035-4_9

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