A hybrid landmark Aalen-Johansen estimator for transition probabilities in partially non-Markov multi-state models

DOI10.1007/S10985-021-09534-4OpenAlexW3203713385MaRDI QIDQ2074091

Rune Hoff, Ingrid S. Mehlum, Odd O. Aalen, Niklas Maltzahn, Jon Michael Gran, Hein Putter

Publication date: 4 February 2022

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2007.00974

zbMATH Keywords

transition probabilitiesAalen-Johansen estimatorsick leavelandmarkingnon-Markov multi-state models

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Survival analysis and censored data (62Nxx)

Related Items (3)

Targeted estimation of state occupation probabilities for the non‐Markov illness‐death model ⋮ Extension of as-if-Markov modeling to scaled payments ⋮ Inference for transition probabilities in non-Markov multi-state models

Uses Software

• mstate
• invGauss

Cites Work

• Unnamed Item
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• Survival and event history analysis. A process point of view
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• Multi-state models: A review
• Validity of the Aalen-Johansen estimators of stage occupation probabilities and Nelson-Aalen estimators of integrated transition hazards for non-Markov models
• State occupation probabilities in non-Markov models
• Landmark estimation of transition probabilities in non-Markov multi-state models with covariates
• A survey of product-integration with a view toward application in survival analysis
• Transition probability estimates for non-Markov multi-state models
• Covariate Adjustment of Event Histories Estimated from Markov Chains: The Additive Approach
• Robust Inference for Event Probabilities with Non-Markov Event Data
• Estimation of Integrated Transition Hazards and Stage Occupation Probabilities for Non-Markov Systems Under Dependent Censoring
• Nonparametric estimation of transition probabilities in the non‐Markov illness‐death model: A comparative study
• Multi-state models for event history analysis
• Statistical models based on counting processes

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