Methods for predictive models with longitudinal data

纵向数据预测模型的方法

• 批准号: RGPIN-2019-04296
• 负责人: Dubin, Joel
• 金额: $ 1.31万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=676903
• 关键词: Methods; predictive; models; longitudinal; data

Accurate prediction of future outcomes is a common goal in many areas of science (e.g., climate, earthquake, hydrology, medical, etc.). The goal in my research program is to develop new methods for prediction problems where data that are collected over time, i.e., longitudinal data, are used to help predict future events. ******My research program specifically focuses on the prediction of short-term events (within weeks or even days), with an eye on applications where there is potential saving of forests, or property, or life, etc., and for which early and sufficiently accurate predictions are of importance. A key trade-off in predicting future events is to balance the accuracy that predictions can have if following time-varying information right to the point that the event is about to occur, as opposed to making an early prediction before it is too late (as the event is imminent). For example, if prevailing winds suggest there is a certain positive probability that a large forest fire may engulf a proximal town in a couple of days, at what point does a decision for an evacuation take place, especially when there is also a chance for predicting a false positive event. Similar decisions can be important in the context of other events, such as earthquakes, volcanoes, hurricanes, and heat waves. Here, we would like to develop a decision-making process that appropriately accommodates the trade-off between (a) early decisions that may prevent injury or save life but also may lead to a higher rate of false positives and (b) later decisions that are more accurate (i.e., fewer false positives) but may lead to greater loss of quality-of-life or actual life. We need to also consider possible false negative decisions, i.e., by deciding not to act due to, for example, assuming the probability of an event is sufficiently low, but thereafter the event actually occurs. We can consider this entire decision-making process in terms of cost, and we would obviously like to minimize this cost. Various assumptions need to be made, including on probabilities and costs of false positives and false negatives, respectively. Comprehensive simulation studies will be a key component of this work, and we will find and analyze relevant real data sources (e.g., daily temperature and rainfall datasets) as well. In both simulations and real datasets, we will evaluate the accuracy of our predictions, both in absence of consideration of cost and in presence of different assumptions about costs. ******As mentioned above, this research work has relevance across various disciplines, including in statistics, and potentially environmental, hydrological, biological, and atmospheric sciences, among others. The findings that my trainees and I will produce will be useful for researchers in Canada and beyond, due to the ever-increasing need to properly predict future events, and to place proper costs on making incorrect decisions.**

对未来结果的准确预测是许多科学领域（如气候、地震、水文、医学等）的共同目标。我的研究计划的目标是开发预测问题的新方法，在这些问题中，随着时间的推移收集的数据，即纵向数据，用于帮助预测未来事件。******我的研究项目特别关注短期事件（几周甚至几天内）的预测，着眼于有可能拯救森林、财产或生命等的应用，因此早期和足够准确的预测是很重要的。预测未来事件的一个关键权衡是平衡预测的准确性，如果遵循时变信息，直到事件即将发生，而不是在为时已晚之前进行早期预测（因为事件即将发生）。例如，如果盛行风表明有一定的可能性，一场大型森林火灾可能会在几天内吞没附近的城镇，在什么时候做出疏散的决定，特别是当还有机会预测假阳性事件时。在地震、火山爆发、飓风和热浪等其他事件的背景下，类似的决定可能很重要。在这里，我们想开发一个决策过程，适当地适应(a)早期决策可能会防止伤害或挽救生命，但也可能导致更高的误报率；(b)后期决策更准确（即，更少的误报），但可能导致更大的生活质量或实际生活的损失。我们还需要考虑可能的假否定决策，例如，由于假设事件的概率足够低而决定不采取行动，但此后事件实际上发生了。我们可以从成本的角度来考虑整个决策过程，我们显然希望将成本最小化。需要做出各种假设，包括假阳性和假阴性的概率和成本。全面的模拟研究将是这项工作的关键组成部分，我们也将找到并分析相关的真实数据源（例如，每日温度和降雨量数据集）。在模拟和真实数据集中，我们将在不考虑成本和存在不同成本假设的情况下评估我们预测的准确性。******如上所述，这项研究工作涉及各个学科，包括统计学，以及潜在的环境、水文、生物和大气科学等。由于对正确预测未来事件的需求日益增长，以及对做出错误决策的适当成本的需求不断增加，我和我的学员将产生的研究结果将对加拿大及其他地区的研究人员有用