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Accelerated failure time regression for backward recurrence times and current durations

Author

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  • Keiding, Niels
  • Fine, Jason P.
  • Hansen, Oluf H.
  • Slama, Rémy

Abstract

Backward recurrence times in stationary renewal processes and current durations in dynamic populations observed at a cross-section may yield estimates of underlying interarrival times or survival distributions under suitable stationarity assumptions. Regression models have been proposed for these situations, but accelerated failure time models have the particularly attractive feature that they are preserved when going from the backward recurrence times to the underlying survival distribution of interest. This simple fact has recently been noticed in a sociological context and is here illustrated by a study of current duration of time to pregnancy.

Suggested Citation

  • Keiding, Niels & Fine, Jason P. & Hansen, Oluf H. & Slama, Rémy, 2011. "Accelerated failure time regression for backward recurrence times and current durations," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 724-729, July.
    • Handle: RePEc:eee:stapro:v:81:y:2011:i:7:p:724-729
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    References listed on IDEAS

    as
    1. Mohamed M. Ali & Tom Marshall & Abdel G. Babiker, 2001. "Analysis of incomplete durations with application to contraceptive use," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(3), pages 549-563.
    2. Stephen R. Cosslett, 2004. "Efficient Semiparametric Estimation of Censored and Truncated Regressions via a Smoothed Self-Consistency Equation," Econometrica, Econometric Society, vol. 72(4), pages 1277-1293, July.
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    Cited by:

    1. Yu Shen & Jing Ning & Jing Qin, 2017. "Nonparametric and semiparametric regression estimation for length-biased survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 3-24, January.
    2. J. H. McVittie & D. B. Wolfson & D. A. Stephens, 2020. "Parametric modelling of prevalent cohort data with uncertainty in the measurement of the initial onset date," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 389-401, April.
    3. Niels Keiding & Katrine Lykke Albertsen & Helene Charlotte Rytgaard & Anne Lyngholm Sørensen, 2019. "Prevalent cohort studies and unobserved heterogeneity," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(4), pages 712-738, October.
    4. Pourab Roy & Jason P. Fine & Michael R. Kosorok, 2022. "Efficiency of naive estimators for accelerated failure time models under length‐biased sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 525-541, June.

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