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: 7940480
• 负责人: Joan G. Staniswalis
• 金额: $ 11.21万
• 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/7940480
• 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; 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）：该提案着重于扩展主要差分分析（PDA），以分析曲线数据。听觉研究中的几种应用正在激发这种方法论扩展，从而可以进行协变量调整。当前，所有已发表的方法用于分析听觉脑干响应曲线（ABR）和皮质听觉诱发潜在曲线（CAEP）描述曲线的特征，例如突出波形的位置和振幅。所提出的统计方法将允许分析使用整个ABR和CAEP曲线，而不是仅仅选定的特征，从而有助于理解与年龄相关的，多发性硬化症或糖尿病相关的听觉刺激的变化，并更好地预测来自神灵植入的临床临床量产。该方法有可能用于早期检测脑外伤（TBI）。了解噪声引起的听力损失和TBI的相互作用，伊拉基自由行动/行动持久的自由士兵所常见的疾病（Meyers，Wilmington，Gallun和Henry 2009; Jordan，Lee and Lee and Helfer 2009）在此期间在这段时间内正在进行伊拉克和伊拉克人的军事人员部署。 PDA是通过首先估计接近歼灭嘈杂曲线数据的线性差分运算符来获得曲线低维表示的方法。在特定的目标（1）中，将扩展主差分分析，包括使用局部线性平滑的协变量调整。该系数函数的非参数估计量的渐近偏差和方差特性将进行分析研究。偏差和方差的渐近表达式将用于提出基于数据的方法来平滑参数选择。提出了协变量意义的测试统计数据。在特定目标（2）中，开发的方法将在SPLU或R之一中实施，并公开可用。将执行计算机仿真研究，以验证系数估计值的偏差和方差的渐近理论可用于指导平滑参数选择，并研究拟议的测试统计量的特性。在分析中了解扩展PDA的属性并实施扩展的PDA软件后，将在与听觉研究人员协商时分析特定目标（3）和（4）的听觉研究数据。 PI具有发展性学术和专业目标。学术目标是发展听觉研究的能力，以推进解决该领域数据分析问题的新型统计方法。专业目标是在UTEP上建立强大的研究环境：涉及新计算科学博士学位的博士生。统计学的计划和硕士学生；在研究会议上介绍；并与国家听觉研究专家建立合作。发展目标的进展将根据其在统计数据和最近获得批准的UTEP计算科学计划的指导下的发表率和学生数量的增加来衡量。 1 公共卫生相关性：叙述所提出的统计方法将允许进行统计分析，该分析使用整个听觉脑干反应（ABR）和皮质听觉唤起的潜力（CAEP）曲线，而不仅仅是选定的特征，从而有助于对年龄相关的变化，多发性硬化症或糖尿病相关的群体刺激的临时刺激性临时预测和临时性预测的临时过程中的多个硬化症或糖尿病相关的变化。该方法有可能用于早期检测脑外伤（TBI）。了解噪声引起的听力损失和TBI的相互作用，伊拉基自由行动/行动持久的自由士兵所常见的疾病（Meyers，Wilmington，Gallun和Henry 2009; Jordan，Lee and Lee and Helfer 2009）在此期间在这段时间内正在进行伊拉克和伊拉克人的军事人员部署。