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Article
Confidence Bands for Quantiles As a Function of Covariates in Recurrent Event Models
Canadian Journal of Statistics
  • Akim Adekpedjou, Missouri University of Science and Technology
  • Gayla R. Olbricht, Missouri University of Science and Technology
  • Gideon K. D. Zamba
Abstract

We investigate the construction of various confidence bands for quantiles of the time between event recurrences when covariates and interventions performed after a recurrence are accounted for via a general Cox-type model for recurrent events. We propose three types of bands: those based on the asymptotic properties of the properly standardized quantile; those based on a Khmaladze transformation of the original limiting distribution; and those based on bootstrap techniques. Asymptotic properties of the three types of bands are presented and their small and large sample performances and coverage probabilities are assessed via simulation study.

Department(s)
Mathematics and Statistics
Research Center/Lab(s)
Center for High Performance Computing Research
Keywords and Phrases
  • Bahadur representation,
  • Bootstrap,
  • Confidence bands,
  • Khmaladze transformation,
  • Quantile,
  • Recurrent events
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Statistical Society of Canada / Société statistique du Canada, All rights reserved.
Publication Date
12-1-2018
Publication Date
01 Dec 2018
Citation Information
Akim Adekpedjou, Gayla R. Olbricht and Gideon K. D. Zamba. "Confidence Bands for Quantiles As a Function of Covariates in Recurrent Event Models" Canadian Journal of Statistics Vol. 46 Iss. 4 (2018) p. 610 - 634 ISSN: 0319-5724; 1708-945X
Available at: http://works.bepress.com/gayla-olbricht/53/