Multilevel Structural Equation Models For Longitudinal Data Where Predictors Are Measured More Frequently Than Outcomes: An Application to the Effects of Stress on the Cognitive Function of Nurses
针对生态瞬时评估中预测变量测量频率高于结果变量的数据，提出一种灵活的多水平结构方程模型，并应用于研究压力对电话热线护士认知功能的影响。
Summary Ecological momentary assessment is used to measure subjects' mood and behaviour repeatedly over time, leading to intensive longitudinal data. Variability in ecological momentary assessment schedules creates an analytical challenge because predictors are measured more frequently than responses. We consider this problem in a study of the effect of stress on the cognitive function of telephone helpline nurses, where stress is measured for each call and cognitive outcomes are measured at the end of a shift. We propose a flexible structural equation model which can handle multiple levels of clustering, measurement error, time trends and mixed variable types.