Inference for ranking data

排名数据的推断

• 批准号: 9076-2006
• 负责人: Cabilio, Paul
• 金额: $ 0.87万
• 依托单位: Acadia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=389901
• 关键词: Inference; ranking; data

Consider a situation where patients are being monitored with respect to their responses to a particular treatment. Patients are supposed to report at a clinic at regular times in order that measurements be taken reflecting their health status. It is conjectured that there should be an improvement over a period of time and that this improvement is not constant but that it is only noticeable at certain times. Unfortunately not every patient reports to the clinic at the required times, so there are  missing observations. The object of the analysis is to show, in spite of the missing data, that there has been an improvement over the monitored times, and to identify those times at which improvement is marked and significant. Consider also the situation where patients are required to take medications over a period of time for a particular ailment. Not all patients are careful in following the required schedules for the taking of medications particularly if there are combinations of different  medications that must be taken at different times, nor do all patients comply with the prescribed activities that may be part of the regime. In order to determine the success of different  methods (such as written material, one-on-one instruction, etc.) for educating patients as to their condition, their medication requirements and related activities, patients are divided into several groups in which different methods were used to impart information and conduct training. After a certain period of time has elapsed, patients in these groups are given questionnaires relating to their level of understanding. It is desired to compare the level of comprehension between the groups, in the light of the fact that not all patients answer all questions. These scenarios are examples of direct applications of the anticipated results of my proposed research in Inference for Ranking Data.

考虑这样一种情况：正在监测患者对特定治疗的反应。病人应该定期到诊所报到，以便进行反映其健康状况的测量。应当强调的是，在一段时间内应该有改善，这种改善不是恒定的，而是只有在某些时候才明显。不幸的是，并不是每个病人都在规定的时间到诊所报到，所以有观察结果缺失。分析的目的是表明，尽管数据缺失，但在监测时间内已有所改善，并确定改善明显和显著的时间。还要考虑患者需要在一段时间内服用药物治疗特定疾病的情况。并非所有患者都认真遵循所需的服药时间表，特别是如果必须在不同时间服用不同药物的组合，也不是所有患者都遵守可能是该方案一部分的规定活动。为了确定不同方法（如书面材料、一对一指导等）的成功与否，为了教育病人了解他们的病情，他们的药物需求和相关活动，病人被分成几组，其中使用不同的方法来传授信息和进行培训。经过一段时间后，这些组中的患者会收到与他们的理解水平有关的问卷。考虑到并非所有患者都回答了所有问题，希望比较各组之间的理解水平。这些场景是我在排名数据推理中提出的研究的预期结果的直接应用的例子。