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Choice of time scale for analysis of recurrent events data

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  • Philip Hougaard

    (Biometrics, Lundbeck)

Abstract

Recurrent events refer to events that over time can occur several times for each individual. Full use of such data in a clinical trial requires a method that addresses the dependence between events. For modelling this dependence, there are two time scales to consider, namely time since start of the study (running time) or time since most recent event (gap time). In the multi-state setup, it is possible to estimate parameters also in the case, where the hazard model allows for an effect of both time scales, making this an extremely flexible approach. However, for summarizing the effect of a treatment in a transparent and informative way, the choice of time scale and model requires much more care. This paper discusses these choices both from a theoretical and practical point of view. This is supported by a simulation study showing that in a frailty model with assumptions covered by both time scales, the gap time approach may give misleading results. A literature dataset is used for illustrating the issues.

Suggested Citation

  • Philip Hougaard, 2022. "Choice of time scale for analysis of recurrent events data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(4), pages 700-722, October.
    • Handle: RePEc:spr:lifeda:v:28:y:2022:i:4:d:10.1007_s10985-022-09569-1
    DOI: 10.1007/s10985-022-09569-1
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    References listed on IDEAS

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    1. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    2. Rondeau, Virginie & Marzroui, Yassin & Gonzalez, Juan R., 2012. "frailtypack: An R Package for the Analysis of Correlated Survival Data with Frailty Models Using Penalized Likelihood Estimation or Parametrical Estimation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i04).
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