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Robust Inference for Event Probabilities with Non-Markov Event Data

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  • David V. Glidden

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  • David V. Glidden, 2002. "Robust Inference for Event Probabilities with Non-Markov Event Data," Biometrics, The International Biometric Society, vol. 58(2), pages 361-368, June.
    • Handle: RePEc:bla:biomet:v:58:y:2002:i:2:p:361-368
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2002.00361.x
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    References listed on IDEAS

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    1. Datta, Somnath & Satten, Glen A., 2001. "Validity of the Aalen-Johansen estimators of stage occupation probabilities and Nelson-Aalen estimators of integrated transition hazards for non-Markov models," Statistics & Probability Letters, Elsevier, vol. 55(4), pages 403-411, December.
    2. Somnath Datta & Glen A. Satten & Susmita Datta, 2000. "Nonparametric Estimation for the Three-Stage Irreversible Illness–Death Model," Biometrics, The International Biometric Society, vol. 56(3), pages 841-847, September.
    3. Niels Keiding & Per Kragh Andersen, 1989. "Nonparametric Estimation of Transition Intensities and Transition Probabilities: A Case Study of a Two‐State Markov Process," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(2), pages 319-329, June.
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    Cited by:

    1. Giorgos Bakoyannis & Dipankar Bandyopadhyay, 2022. "Nonparametric tests for multistate processes with clustered data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(5), pages 837-867, October.
    2. Niklas Maltzahn & Rune Hoff & Odd O. Aalen & Ingrid S. Mehlum & Hein Putter & Jon Michael Gran, 2021. "A hybrid landmark Aalen-Johansen estimator for transition probabilities in partially non-Markov multi-state models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(4), pages 737-760, October.
    3. Jacobo de Uña-Álvarez & Luís Meira-Machado, 2015. "Nonparametric estimation of transition probabilities in the non-Markov illness-death model: A comparative study," Biometrics, The International Biometric Society, vol. 71(2), pages 364-375, June.
    4. Tobias Bluhmki & Dennis Dobler & Jan Beyersmann & Markus Pauly, 2019. "The wild bootstrap for multivariate Nelson–Aalen estimators," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(1), pages 97-127, January.
    5. Jan Beyersmann & Hein Putter, 2014. "A note on computing average state occupation times," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(62), pages 1681-1696.
    6. Arthur Allignol & Martin Schumacher & Jan Beyersmann, 2011. "Estimating summary functionals in multistate models with an application to hospital infection data," Computational Statistics, Springer, vol. 26(2), pages 181-197, June.
    7. Nießl, Alexandra & Allignol, Arthur & Beyersmann, Jan & Mueller, Carina, 2023. "Statistical inference for state occupation and transition probabilities in non-Markov multi-state models subject to both random left-truncation and right-censoring," Econometrics and Statistics, Elsevier, vol. 25(C), pages 110-124.
    8. Rune Hoff & Hein Putter & Ingrid Sivesind Mehlum & Jon Michael Gran, 2019. "Landmark estimation of transition probabilities in non-Markov multi-state models with covariates," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(4), pages 660-680, October.

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