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Conditional Aalen--Johansen estimation

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arxiv 2303.02119 v3 pith:PVDMI7HQ submitted 2023-03-03 math.ST stat.MEstat.TH

classification math.STstat.MEstat.TH
keywords estimatorconditionalprocessaalen--johansenconditioningallowinganalysisapplicable
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The conditional Aalen--Johansen estimator, a general-purpose non-parametric 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.

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  1. Markov Renewal Proportional Hazards is All You Need

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    A mostly tutorial and application paper claims semi-Markov models with the DSH estimator produce smoother transition probability curves than Aalen-Johansen in the EBMT stem cell transplant data, without quantitative v...

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