Statistical Methods on Challenging Issues of Biosciences

统计科学对自然科学和工程学发展的重要性怎么强调都不为过。几乎每个领域的进步，包括先进技术、环境科学、制造业、农业和生命科学，最终都取决于统计方面的发展。统计和生物统计科学中的新方法在许多现代科学、金融、经济和生命科学中发挥着核心作用，这些科学、金融、经济和生命科学严重依赖于从海量数据中提取信息。随着科学和工程的进步，数据的新特征不断涌现，传统的统计方法已不足以应对这些挑战。现有的方法通常是在数据“完美”的“理想”假设下开发出来的。然而，在现实中，用来进行科学推断的数据远非“完美”。测量误差和缺失值无处不在地与数据联系在一起，它们通常会破坏常用的统计方法。尽管不断增长的文献和新兴的词汇已经提高了人们对“不完美”数据对统计推断和应用的关键影响的认识，但处理“不完美”数据的有效方法仍然缺乏。我的研究的主要目标是开发创新和严格的统计方法，以解决由“不完美”数据引发的各种挑战性问题。将制定灵活的建模策略和有效的推理方法，以解决有关测量误差和遗漏观测的基本问题。拟议的研究将提供新的见解和有价值的结果，使研究人员和行业合作伙伴都受益。预期的好处包括在提高方法标准和在受高度影响的领域提供广泛的应用方面产生相当显著的效果。这将对我们的社会产生重大的直接和积极的经济影响。

It is difficult to overemphasize the importance of statistical science to the development of the naturalsciences and engineering. Advances in virtually every field, including advanced technologies, environmentalscience, manufacturing, agriculture, and life sciences, ultimately depend on statistical developments. Novel methods in statistical and biostatistical sciences occupy a central role in much of the modern sciences, finance, economics and life sciences that heavily rely on drawing information from massive data.As sciences and engineering advance, new features of data emerge and traditional statistical methods become inadequate to handle those challenges. Existing methods have often been developed under the "ideal" assumption that data are "perfect". In reality, however, data from which scientific inference is drawn are far from "perfect". Measurement error and missing values are ubiquitously associated with data and they typically break down usual statistical methods. Although the growing literature and emerging lexicon have raised awareness of the critical impact that "imperfect" data can have on statistical inference and applications, effective methods on handling "imperfect" data remain elusive.The primary objective of my research is to develop innovative and rigorous statistical methodology to tackle various challenging problems induced by "imperfect" data. Flexible modeling strategies and valid inference methods will be developed to address fundamental issues concerning measurement error and missing observations. The proposed research will provide new insights and valuable results that will benefit both researchers and industrial partners. The anticipated benefits include a considerably marked effect on both enhancing methodological standards and providing a broad range of applications in highly impacted fields. This will lead a significantly direct and positive economic impact on our society.