Survival and Reliability Models with High Dimensional Data
具有高维数据的生存和可靠性模型
基本信息
- 批准号:RGPIN-2017-04537
- 负责人:
- 金额:$ 1.17万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2022
- 资助国家:加拿大
- 起止时间:2022-01-01 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This proposal deals with novel methods and models to describe time to event data. Areas of application include engineering reliability, medical statistics and others. For example, in medical statistics, models for clinical trial data, which include estimation of time to cure of patients with C.Difficile is of current interest. In engineering the time for a dominant crack to develop to a critical size resulting in failure due to metal fatigue is also of interest. I am particularly interested in failure or event time models, which are based on a plausible underlying model of the process, which actually produces failure. The most popular model for event time data is the Cox model. While this has been very useful, Cox himself has expressed doubts about its possible overuse (Statistical Science, Reid 1994). An important aspect of this model, and more general counting process models, is that they focus on purely empirical models of the hazard function. Earlier research, including some of my own, in the engineering reliability area, suggests that considerable subject matter knowledge in, for example, failure due to metal fatigue, is usually more convincing to applied scientists.I consider several models, which have an underlying process-based origin. The process may measure cumulative damage in an engineering context or a putative measure of human health in a medical context. The Birnbaum-Saunders fatigue life model arises from a stochastic model of the growth of a dominant crack eventually leading to catastrophic failure. It is related to a class of models referred to as First Hitting Time (FHT). The underlying process in this case may be a Wiener process (see Lee and Whitmore 2006). I propose to work with variants of Wiener process based models, as well as the Birnbaum-Saunders model. I will develop novel methods to deal with high-dimensional (HD) covariate data for both of these models; an example is microbiome data, in which the covariate space relates to very HD next generation sequencing data on clinical trial participants. Another issue I will study is random effects versions of these models.This can be used for clustered data or as an alternative to multiplicative frailty models for Cox PH. The latter model has flaws, in that the PH assumption may fail and also multiplicative frailty is not entirely convincing, Aalen et al (2008). I will develop novel methods for a variety of cure rate models based on FHTs. Similar models are very useful in engineering reliability. These threshold models are an exciting alternative to models such as the well-studied Cox model, frequently used in medical statistics, or the accelerated failure time model, which is popular in engineering reliability. There is great scope for new methodological development and applications of these new models to real scientific and technological problems. This is a very exciting alternative paradigm to more conventional modeling approaches.
该建议涉及新的方法和模型来描述事件数据的时间。应用领域包括工程可靠性、医疗统计等。例如,在医学统计学中,临床试验数据的模型,其中包括艰难梭菌患者治愈时间的估计,是当前感兴趣的。在工程中,主要裂纹发展到临界尺寸导致由于金属疲劳而失效的时间也是令人感兴趣的。我对失败或事件时间模型特别感兴趣,这些模型基于过程的合理基础模型,实际上会产生失败。事件时间数据最流行的模型是考克斯模型。虽然这是非常有用的,但考克斯本人对它可能被过度使用表示怀疑(Statistical Science,Reid 1994)。这个模型和更一般的计数过程模型的一个重要方面是,它们专注于风险函数的纯经验模型。早期的研究,包括我自己的一些,在工程可靠性领域,表明相当多的主题知识,例如,由于金属疲劳失效,通常是更有说服力的应用scients.I考虑几个模型,其中有一个基本的过程为基础的起源。该过程可以测量工程背景下的累积损伤或医学背景下的人类健康的推定测量。Birnbaum-Saunders疲劳寿命模型源于主导裂纹增长的随机模型,最终导致灾难性失效。它与一类称为首次命中时间(FHT)的模型有关。在这种情况下,潜在的过程可能是维纳过程(参见Lee和Whitmore 2006)。我建议使用基于Wiener过程的模型以及Birnbaum-Saunders模型的变体。我将开发新的方法来处理这两个模型的高维(HD)协变量数据;一个例子是微生物组数据,其中协变量空间与临床试验参与者的非常HD的下一代测序数据相关。我将研究的另一个问题是这些模型的随机效应版本。这可以用于聚类数据或作为考克斯PH的乘法脆弱模型的替代方案。后一个模型有缺陷,因为PH假设可能失败,而且乘法脆弱性也不完全令人信服,Aalen et al(2008)。我将开发基于FHT的各种治愈率模型的新方法。相似模型在工程可靠性研究中具有重要的应用价值。这些阈值模型是一个令人兴奋的替代模型,如研究充分的考克斯模型,经常用于医疗统计,或加速失效时间模型,这是流行的工程可靠性。有很大的余地为新的方法的发展和应用这些新的模式,以真实的科学和技术问题。这是一个非常令人兴奋的替代范式更传统的建模方法。
项目成果
期刊论文数量(0)
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{{ truncateString('Desmond, Anthony', 18)}}的其他基金
Survival and Reliability Models with High Dimensional Data
具有高维数据的生存和可靠性模型
- 批准号:
RGPIN-2017-04537 - 财政年份:2021
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival and Reliability Models with High Dimensional Data
具有高维数据的生存和可靠性模型
- 批准号:
RGPIN-2017-04537 - 财政年份:2020
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival and Reliability Models with High Dimensional Data
具有高维数据的生存和可靠性模型
- 批准号:
RGPIN-2017-04537 - 财政年份:2019
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival and Reliability Models with High Dimensional Data
具有高维数据的生存和可靠性模型
- 批准号:
RGPIN-2017-04537 - 财政年份:2018
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival and Reliability Models with High Dimensional Data
具有高维数据的生存和可靠性模型
- 批准号:
RGPIN-2017-04537 - 财政年份:2017
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival analysis and estimating functions
生存分析和估计功能
- 批准号:
8736-2011 - 财政年份:2015
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival analysis and estimating functions
生存分析和估计功能
- 批准号:
8736-2011 - 财政年份:2014
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival analysis and estimating functions
生存分析和估计功能
- 批准号:
8736-2011 - 财政年份:2013
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival analysis and estimating functions
生存分析和估计功能
- 批准号:
8736-2011 - 财政年份:2012
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
Survival analysis and estimating functions
生存分析和估计功能
- 批准号:
8736-2011 - 财政年份:2011
- 资助金额:
$ 1.17万 - 项目类别:
Discovery Grants Program - Individual
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- 资助金额:
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