Median Analysis of Repeated Measures Associated with Recurrent Events in Presence of Terminal Event

Sundaram Rajeshwari (), Ma Ling and Ghoshal Subhashis
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Sundaram Rajeshwari: Division of Intramural Population Health Research, National Institute of Child Health and Human Development, Rm 3232 6710B Rockledge Dr, Bethesda, MD 20892-2425, USA
Ma Ling: Division of Intramural Population Health Research, National Institute of Child Health and Human Development, Rm 3232 6710B Rockledge Dr, Bethesda, MD 20892-2425, USA
Ghoshal Subhashis: Department of Statistics, North Carolina State University, Raleigh, NC, USA

The International Journal of Biostatistics, 2017, vol. 13, issue 1, 16

Abstract: Recurrent events are often encountered in medical follow up studies. In addition, such recurrences have other quantities associated with them that are of considerable interest, for instance medical costs of the repeated hospitalizations and tumor size in cancer recurrences. These processes can be viewed as point processes, i.e. processes with arbitrary positive jump at each recurrence. An analysis of the mean function for such point processes have been proposed in the literature. However, such point processes are often skewed, leading to median as a more appropriate measure than the mean. Furthermore, the analysis of recurrent event data is often complicated by the presence of death. We propose a semiparametric model for assessing the effect of covariates on the quantiles of the point processes. We investigate both the finite sample as well as the large sample properties of the proposed estimators. We conclude with a real data analysis of the medical cost associated with the treatment of ovarian cancer.

Keywords: recurrent events; quantile regression; informative censoring; estimating equations; survival analysis (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1515/ijb-2016-0057

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