Conditional Aalen–Johansen estimation

Martin Bladt and Christian Furrer

Scandinavian Journal of Statistics, 2025, vol. 52, issue 2, 873-902

Abstract: The conditional Aalen–Johansen estimator, a general‐purpose nonparametric estimator of conditional state occupation probabilities, is introduced. The estimator is applicable for any finite‐state jump process and supports conditioning on external as well as internal covariate information. The conditioning feature permits for a much more detailed analysis of the distributional characteristics of the process. The estimator reduces to the conditional Kaplan–Meier estimator in the special case of a survival model and also englobes other, more recent, landmark estimators when covariates are discrete. Strong uniform consistency and asymptotic normality are established under lax moment conditions on the multivariate counting process, allowing in particular for an unbounded number of transitions.

Date: 2025
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https://doi.org/10.1111/sjos.12774

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Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:52:y:2025:i:2:p:873-902

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