Pattern Recognition of Longitudinal Trial Data with Nonignorable Missingness: An Empirical Case Study.

IF 2.5 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Information Technology & Decision Making Pub Date : 2009-09-01 DOI:10.1142/S0219622009003508

Hua Fang, Kimberly Andrews Espy, Maria L Rizzo, Christian Stopp, Sandra A Wiebe, Walter W Stroup

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引用次数: 0

Abstract

Methods for identifying meaningful growth patterns of longitudinal trial data with both nonignorable intermittent and drop-out missingness are rare. In this study, a combined approach with statistical and data mining techniques is utilized to address the nonignorable missing data issue in growth pattern recognition. First, a parallel mixture model is proposed to model the nonignorable missing information from a real-world patient-oriented study and concurrently to estimate the growth trajectories of participants. Then, based on individual growth parameter estimates and their auxiliary feature attributes, a fuzzy clustering method is incorporated to identify the growth patterns. This case study demonstrates that the combined multi-step approach can achieve both statistical gener ality and computational efficiency for growth pattern recognition in longitudinal studies with nonignorable missing data.

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具有不可忽略遗漏性的纵向试验数据的模式识别：实证案例研究

在纵向试验数据中同时存在不可忽略的间断缺失和辍学缺失的情况下，识别有意义的增长模式的方法并不多见。本研究采用统计和数据挖掘技术相结合的方法来解决生长模式识别中的不可忽略的缺失数据问题。首先，我们提出了一个并行混合模型来模拟真实世界中以患者为导向的研究中不可忽略的缺失信息，并同时估计参与者的生长轨迹。然后，基于单个生长参数估计及其辅助特征属性，采用模糊聚类方法来识别生长模式。该案例研究表明，在具有不可忽略的缺失数据的纵向研究中，多步骤组合方法可以实现生长模式识别的统计通用性和计算效率。

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来源期刊

International Journal of Information Technology & Decision Making 工程技术-计算机：跨学科应用

CiteScore

7.40

自引率

14.30%

发文量

审稿时长

6 months

期刊介绍： International Journal of Information Technology and Decision Making (IJITDM) provides a global forum for exchanging research findings and case studies which bridge the latest information technology and various decision-making techniques. It promotes how information technology improves decision techniques as well as how the development of decision-making tools affects the information technology era. The journal is peer-reviewed and publishes both high-quality academic (theoretical or empirical) and practical papers in the broad ranges of information technology related topics including, but not limited to the following: • Artificial Intelligence and Decision Making • Bio-informatics and Medical Decision Making • Cluster Computing and Performance • Data Mining and Web Mining • Data Warehouse and Applications • Database Performance Evaluation • Decision Making and Distributed Systems • Decision Making and Electronic Transaction and Payment • Decision Making of Internet Companies • Decision Making on Information Security • Decision Models for Electronic Commerce • Decision Models for Internet Based on Companies • Decision Support Systems • Decision Technologies in Information System Design • Digital Library Designs • Economic Decisions and Information Systems • Enterprise Computing and Evaluation • Fuzzy Logic and Internet • Group Decision Making and Software • Habitual Domain and Information Technology • Human Computer Interaction • Information Ethics and Legal Evaluations • Information Overload • Information Policy Making • Information Retrieval Systems • Information Technology and Organizational Behavior • Intelligent Agents Technologies • Intelligent and Fuzzy Information Processing • Internet Service and Training • Knowledge Representation Models • Making Decision through Internet • Multimedia and Decision Making [...]