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

IF 1.2 4区 数学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Rajeshwari Sundaram, Ling Ma, Subhashis Ghoshal
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引用次数: 0

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.

存在终末期事件时与复发事件相关的重复测量的中位数分析。
在医学随访研究中经常遇到复发事件。此外,这种复发还有其他值得关注的数量,例如反复住院的医疗费用和癌症复发时的肿瘤大小。这些过程可以看作点过程,即在每次递归时具有任意正跳跃的过程。对这类点过程的均值函数的分析已经在文献中提出。然而,这样的点过程往往是倾斜的,导致中位数作为一个更合适的措施比平均值。此外,对复发事件数据的分析往往因死亡的存在而复杂化。我们提出了一个半参数模型来评估协变量对点过程分位数的影响。我们研究了所提出的估计量的有限样本和大样本性质。我们以卵巢癌治疗相关医疗费用的真实数据分析作为结论。
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来源期刊
International Journal of Biostatistics
International Journal of Biostatistics MATHEMATICAL & COMPUTATIONAL BIOLOGY-STATISTICS & PROBABILITY
CiteScore
2.10
自引率
8.30%
发文量
28
审稿时长
>12 weeks
期刊介绍: The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.
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