Skip to main content
Log in

Analysis of recurrent events with non-negligible event duration, with application to assessing hospital utilization

  • Published:
Lifetime Data Analysis Aims and scope Submit manuscript

Abstract

In an attempt to provide tools for assessing hospital utilization, this paper extends well-known models for recurrent events to address non-negligible event duration and presents a procedure for estimating the model parameters. The model extension is natural and easy to understand. Asymptotic properties of the associated inferences are derived adapting the well-developed methods based on the counting process formulation. Several specifications of the proposed modeling are illustrated with the hospitalization records of childhood cancer survivors from a health care insurance system that motivated this research. The usefulness and robustness of the proposed approach is demonstrated numerically via simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Andersen PK, Borgan O, Gill RD, Keiding N (1992) Statistical models based on counting processes. Springer, New York

    Google Scholar 

  • Andersen PK, Gill RD (1982) Cox’s regression model for counting processes: a large sample study. Anna Stat 10: 1100–1120

    Article  MATH  MathSciNet  Google Scholar 

  • Cai J, Schaubel DE (2004) Marginal means/rates models for multiple type recurrent event data. Lifetime Data Anal 10: 121–138

    Article  MATH  MathSciNet  Google Scholar 

  • Cook RJ, Lawless JF (2007) The statistical analysis of recurrent events. Springer, New York

    MATH  Google Scholar 

  • Cox DR (1975) Partial likelihood. Biometrika 62: 269–276

    Article  MATH  MathSciNet  Google Scholar 

  • Fleming TR, Harrington DP (1991) Counting processes and survival analysis. Wiley, New York

    Google Scholar 

  • Ghosh D, Lin DY (2003) Semiparametric analysis of recurrent events data in the presence of dependent censoring. Biometrics 59: 877–885

    Article  MATH  MathSciNet  Google Scholar 

  • Grambsch P, Therneau T (1994) Proportional hazards tests and diagnostics based on weighted residuals. Biometrika 81: 515–526

    Article  MATH  MathSciNet  Google Scholar 

  • Kalbfleisch JD, Prentice RL (1980) The statistical analysis of failure time data. Wiley, New York

    MATH  Google Scholar 

  • Kelly PJ, Lim LL-Y (2000) Survival analysis for recurrent event data: an application to childhood infectious diseases. Stat Med 19: 12–33

    Article  Google Scholar 

  • Lawless JF, Nadeau C (1995) Some simple robust methods for the analysis of recurrent events. Technometrics 37: 158–168

    Article  MATH  MathSciNet  Google Scholar 

  • Lee MLT, Whitmore GA (2006) Threshold regression for survival analysis: modeling event times by a stochastic process reaching a boundary. Stat Sci 21: 501–513

    Article  MATH  MathSciNet  Google Scholar 

  • Lin DY, Wei LJ, Yang I, Ying Z (2000) Semiparametric regression for the mean and rate functions of recurrent events. J R Stats Soc, Series B 62: 711–730

    Article  MATH  MathSciNet  Google Scholar 

  • MaCarthur AC, Spinelli JJ, Rogers P, Goddard KJ, Abanto Z, McBride ML (2007a) Mortality among 5-year survivors of cancer diagnosed during childhood or adolescence in British Columbia, Canada. Pediatr Blood Cancer 48(4): 460–467

    Article  MATH  Google Scholar 

  • MaCarthur AC, Spinelli JJ, Rogers P, Goddard KJ, Abanto Z, McBride ML (2007b) Risk of a second malignant neoplasm among 5-year survivors of cancer in childhood and adolescence in British Columbia, Canada. Pediatr Blood Cancer 48(4): 453–459

    Article  Google Scholar 

  • Miloslavsky S, Keles S, van der Laan MJ, Butler S (2004) Recurrent events analysis in the presence of time-dependent covariates and dependent censoring. J R Stats Soc, Series B 66: 239–257

    Article  MATH  Google Scholar 

  • Oakes D (1992) Frailty models for multiple event times. In: Klein J, Goel P (eds) Survival analysis: state of the art. Kluwer, Dordrecht, pp 371–379

    Google Scholar 

  • Pepe MS, Cai J (1993) Some graphical displays and marginal regression analyses for recurrent failure times and time dependent covariates. J Am Stats Assoc 88: 811–820

    Article  MATH  Google Scholar 

  • Prentice RL, Williams BJ, Peterson AV (1981) On the regression analysis of multivariate failure time data. Biometrika 68: 373–379

    Article  MATH  MathSciNet  Google Scholar 

  • Sun J (2006) The statistical analysis of interval-censored failure time data. Springer, New York

    MATH  Google Scholar 

  • Therneau T, Grambsch P (2000) Modeling survival data: extending the cox model. Springer, New York

    MATH  Google Scholar 

  • Twisk JWR, Smidt N, de Vente W (2005) Applied analysis of recurrent events: a practical overview. J Epidemiol Community Health 59: 706–710

    Article  Google Scholar 

  • Wang MC, Qin J, Chiang CT (2001) Analyzing recurrent event data with informative censoring. J Am Stats Assoc 96: 1057–1065

    Article  MATH  MathSciNet  Google Scholar 

  • Ying SC (2006) Generalized longitudinal data analysis, with application to evaluating hospital utilization based on administrative database. Master’s Thesis, Department of Statistics and Actuarial Science, Simon Fraser University

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to X. Joan Hu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hu, X.J., Lorenzi, M., Spinelli, J.J. et al. Analysis of recurrent events with non-negligible event duration, with application to assessing hospital utilization. Lifetime Data Anal 17, 215–233 (2011). https://doi.org/10.1007/s10985-010-9183-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10985-010-9183-8

Keywords

Navigation