线性混合效应模型在人在回路模拟实验分析中的应用

Q2 Social Sciences
Bernd Lorenz, Catherine Chalon-Morgan, I. De Visscher, Thomas Feuerle
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引用次数: 0

摘要

实时人在环路(HITL)模拟是空中交通管理运行概念开发生命周期中的一项重要验证活动。然而,在规划 HITL 模拟时,研究人员面临着一系列实验设计限制,这些限制往往会限制高级统计数据分析的应用。线性混合效应建模(LMEM)是一种多元回归分析技术,在考虑重复测量数据中存在的协方差时相对灵活。本文旨在让航空研究领域的应用研究人员,尤其是应用 HITL 的研究人员更好地了解 LMEM。为此,本文以空客 320 飞行模拟研究中获得的数据为基础,解释了 LMEM 的构建步骤、输出和模型拟合测试,该研究考察了最终进近或起飞路径上两种不同的尾流分离方案对飞行员感知尾流涡流冲击严重程度的影响。实验设置涉及六个未完全交叉的实验因素,每个飞行员的重复次数不平衡,并且包含缺失数据。因此无法使用更传统的重复测量方差分析。LMEM 能够处理这种情况,并能明确地对研究假设进行统计检验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Linear Mixed-Effect Modeling for the Analysis of Human-in-the-Loop Simulation Experiments
A real-time human-in-the-loop (HITL) simulation is a crucial validation activity in the life cycle of air traffic management operational concept development. When planning HITL simulations, however, researchers face a series of experimental design constraints that often limit the application of advanced statistical data analyses. Linear mixed-effects modeling (LMEM) is a multiple regression analysis technique that is comparatively flexible in considering the covariance present in repeated measures data. This paper aims to make LMEM better known to applied researchers in the field of aviation research, particularly those applying HITL. For this purpose, the building steps of LMEM, the output, and model-fit tests are explained based on data obtained from an Airbus 320 flight simulation study that examined the impact of two different wake separation schemes on either a final approach or a departure path on the pilots’ perceived severity of a wake-vortex impact. The experimental setup involved six experimental factors that were not fully crossed, had an unbalanced number of repeats per pilot, and contained missing data. This prevented the use of the more traditional repeated measures analysis of variance. The LMEM was able to handle this and could explicitly test the study hypotheses with statistical confidence.
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来源期刊
Journal of Air Transportation
Journal of Air Transportation Social Sciences-Safety Research
CiteScore
2.80
自引率
0.00%
发文量
16
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