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Empirical Transition Matrix of Multi-State Models: The etm Package

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  • Allignol, Arthur
  • Schumacher, Martin
  • Beyersmann, Jan

Abstract

Multi-State models provide a relevant framework for modelling complex event histories. Quantities of interest are the transition probabilities that can be estimated by the empirical transition matrix, that is also referred to as the Aalen-Johansen estimator. In this paper, we present the R package etm that computes and displays the transition probabilities. etm also features a Greenwood-type estimator of the covariance matrix. The use of the package is illustrated through a prominent example in bone marrow transplant for leukaemia patients.

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  • Allignol, Arthur & Schumacher, Martin & Beyersmann, Jan, 2011. "Empirical Transition Matrix of Multi-State Models: The etm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 38(i04).
    • Handle: RePEc:jss:jstsof:v:038:i04
    DOI: http://hdl.handle.net/10.18637/jss.v038.i04
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    Cited by:

    1. Timothy K Marcella & Scott M Gende & Daniel D Roby & Arthur Allignol, 2017. "Disturbance of a rare seabird by ship-based tourism in a marine protected area," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-23, May.
    2. Ritesh Ramchandani & Dianne M. Finkelstein & David A. Schoenfeld, 2020. "Estimation for an accelerated failure time model with intermediate states as auxiliary information," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 1-20, January.
    3. Pablo Mart�nez-Camblor & Jacobo de U�a-�lvarez & Carmen D�az Corte, 2015. "Expanded renal transplantation: a competing risk model approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(12), pages 2539-2553, December.
    4. Touraine, Célia & Gerds, Thomas A. & Joly, Pierre, 2017. "SmoothHazard: An R Package for Fitting Regression Models to Interval-Censored Observations of Illness-Death Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i07).
    5. Dennis Dobler & Markus Pauly, 2018. "Bootstrap- and permutation-based inference for the Mann–Whitney effect for right-censored and tied data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 639-658, September.
    6. Tobias Bluhmki & Claudia Schmoor & Dennis Dobler & Markus Pauly & Juergen Finke & Martin Schumacher & Jan Beyersmann, 2018. "A wild bootstrap approach for the Aalen–Johansen estimator," Biometrics, The International Biometric Society, vol. 74(3), pages 977-985, September.
    7. Paul Blanche, 2020. "Confidence intervals for the cumulative incidence function via constrained NPMLE," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 45-64, January.
    8. Frans Willekens & Hein Putter, 2014. "Software for multistate analysis," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(14), pages 381-420.
    9. 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.

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