SCORE: Principal Differential Analysis with Covariates for Functional Data

SCORE：函数数据协变量的主微分分析

• 批准号: 8136309
• 负责人: Joan G. Staniswalis
• 金额: $ 11.1万
• 依托单位: UNIVERSITY OF TEXAS EL PASO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8136309
• 关键词: Afghanistan; Age; Aging; Area; Auditory; Auditory Brainstem Responses; Auditory Evoked Potentials; Auditory system; Blast Cell; Brain Stem; Clinical; Cochlear Implants; Cochlear implant procedure; Collaborations; Computational Science; Computer Simulation; Computer software; Consultations; Data; Data Analyses; Databases; Development; Diabetes Mellitus; Disease; Doctor of Philosophy; Early Diagnosis; Environment; Evolution; Freedom; Glucose; Hearing; Hearing Impaired Persons; Iraq; Jordan; Location; Measures; Methodology; Methods; Military Personnel; Modeling; Multiple Sclerosis; Noise-Induced Hearing Loss; Outcome; Process; Property; Publications; Publishing; Recommendation; Reporting; Research; Research Personnel; Sampling; Serum; Severity of illness; Soldier; Statistical Methods; Students; Testing; Time; Transplantation; Traumatic Brain Injury; age related; auditory stimulus; diabetic; disability; experience; graduate student; hearing impairment; novel; operation; programs; public health relevance; statistics; symposium; theories; vector

DESCRIPTION (provided by applicant): This proposal focuses on extending principal differential analysis (PDA) for analysis of curve data. Several applications in auditory research are motivating this methodological extension, which allows for covariate adjustment. Currently, all published methods for analysis of auditory brainstem response curves (ABR) and cortical auditory evoked potential curves (CAEP) describe features of the curve, such as location and amplitude of prominent waveforms. The proposed statistical methods will allow for an analysis that uses the entire ABR and CAEP curves, rather than just selected features, to contribute to the understanding of age-related, multiple sclerosis- or diabetes-related changes in temporal processing of auditory stimuli, and better prediction of clinical outcomes from cochlear implantation. The methods have the potential to be used for the early detection of traumatic brain injury (TBI). Understanding the interaction of noise induced hearing loss and TBI, disorders common to Operation Iraqui Freedom/Operation Enduring Freedom soldiers exposed to explosive blasts (Meyers, Wilmington, Gallun, and Henry 2009; Jordan, Lee, and Helfer 2009), is vital during this time of ongoing deployment of military personnel in Iraq and Afghanistan. PDA is a method for obtaining a low-dimensional representation of a curve by first estimating a linear differential operator that comes close to annihilating the noisy curve data. In Specific Aim (1), principal differential analysis will be extended to include covariate adjustments using local linear smoothing. The asymptotic bias and variance properties of the nonparametric estimators of the coefficient functions will be investigated analytically. The asymptotic expressions for bias and variance will be used to propose data-based methods for smoothing parameter selection. Test statistics for the significance of covariates are proposed. In Specific Aim (2), the methods developed will be implemented in one of Splus or R and made publicly available. Computer simulation studies will be executed to verify that the asymptotic theory for the bias and variance of the estimators of the coefficients is useful in guiding the smoothing parameter selection, and for studying the properties of the proposed test statistics. After the properties of the extended PDA are understood analytically and the extended PDA software is implemented, auditory research data will be analyzed for Specific Aims (3) and (4) in consultation with auditory researchers. The PI has developmental scholarly and professional objectives. The scholarly objective is to develop competency in auditory research in order to advance novel statistical methodologies that solve data analysis problems in the field. The professional objective is to build a strong research environment in statistics at UTEP by: involving doctoral students from the new Computational Sciences Ph.D. program and masters students in statistics; presenting at research conferences; and establishing collaborations with national experts in auditory research. Progress on developmental objectives will be measured in terms of an increased publication rate and numbers of student theses under her direction in statistics and within the recently approved Computational Sciences Program at UTEP. 1 PUBLIC HEALTH RELEVANCE: Narrative The proposed statistical methods will allow for a statistical analysis that uses the entire auditory brainstem response (ABR) and cortical auditory evoked potential (CAEP) curves, rather than just selected features, to contribute to the understanding of age-related changes, multiple sclerosis- or diabetes-related changes in temporal processing of auditory stimuli, and better prediction of clinical outcomes from cochlear implantation. The methods have the potential to be used for the early detection of traumatic brain injury (TBI). Understanding the interaction of noise induced hearing loss and TBI, disorders common to Operation Iraqui Freedom/Operation Enduring Freedom soldiers exposed to explosive blasts (Meyers, Wilmington, Gallun, and Henry 2009; Jordan, Lee, and Helfer 2009), is vital during this time of ongoing deployment of military personnel in Iraq and Afghanistan.

描述（由申请人提供）：本提案侧重于扩展主微分分析（PDA）用于分析曲线数据。听觉研究中的几个应用程序是激励这种方法的扩展，它允许协变量调整。目前，所有已发表的用于分析听觉脑干反应曲线（ABR）和皮层听觉诱发电位曲线（CAEP）的方法都描述了曲线的特征，例如突出波形的位置和幅度。拟议的统计方法将允许使用整个ABR和CAEP曲线，而不仅仅是选定的功能，有助于理解年龄相关的，多发性硬化症或糖尿病相关的听觉刺激时间处理的变化，以及更好地预测人工耳蜗植入的临床结果的分析。该方法有可能用于创伤性脑损伤（TBI）的早期检测。了解噪声性听力损失与创伤性脑损伤的相互作用，创伤性脑损伤是“自由行动”/“持久自由行动”士兵暴露于爆炸性爆炸的常见疾病（Meyers、威尔明顿、加伦和亨利，2009年; Jordan、Lee和Helfer，2009年），在伊拉克和阿富汗持续部署军事人员期间至关重要。PDA是一种通过首先估计接近消除噪声曲线数据的线性微分算子来获得曲线的低维表示的方法。在特定目标（1）中，将扩展主微分分析，以包括使用局部线性平滑的协变量调整。将分析研究系数函数的非参数估计的渐近偏差和方差性质。偏差和方差的渐近表达式将用于提出基于数据的平滑参数选择方法。提出了协变量显著性的检验统计量。在具体目标（2）中，开发的方法将在Splus或R中实现，并公开提供。计算机模拟研究将执行，以验证的渐近理论的偏差和方差的估计系数是有用的指导平滑参数的选择，并研究拟议的测试统计量的性质。在通过分析理解了扩展PDA的属性并实现了扩展PDA软件之后，将与听觉研究人员协商，针对特定目标（3）和（4）分析听觉研究数据。PI具有发展性的学术和专业目标。学术目标是发展听觉研究的能力，以推进新的统计方法，解决该领域的数据分析问题。专业目标是通过以下方式在UTEP建立强大的统计研究环境：涉及来自新计算科学博士的博士生。计划和硕士生在统计;在研究会议上提出;并建立与国家专家在听觉研究的合作。发展目标的进展将根据她在统计学方面的指导下以及最近批准的UTEP计算科学计划中的学生论文数量和出版率的增加来衡量。1 公共卫生相关性：叙述所提出的统计方法将允许使用整个听觉脑干反应（ABR）和皮层听觉诱发电位（CAEP）曲线的统计分析，而不仅仅是选定的功能，有助于理解年龄相关的变化，多发性硬化症或糖尿病相关的听觉刺激时间处理的变化，以及更好地预测人工耳蜗植入的临床结果。该方法有可能用于创伤性脑损伤（TBI）的早期检测。了解噪声性听力损失与创伤性脑损伤的相互作用，创伤性脑损伤是“自由行动”/“持久自由行动”士兵暴露于爆炸性爆炸的常见疾病（Meyers、威尔明顿、加伦和亨利，2009年; Jordan、Lee和Helfer，2009年），在伊拉克和阿富汗持续部署军事人员期间至关重要。