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. (10th March 2016)

• Record Type: Journal Article
• Authors: Steele, Fiona; Clarke, Paul; Leckie, George; Allan, Julia; Johnston, Derek
• Is Part Of: Journal of the Royal Statistical Society. Volume 180:Number 1(2017:Jan.)
• Page Start: 263
• Page End: 283
• Publication Date: 2016-03-10
• Subjects: Ecological momentary assessment -- High frequency data -- Intensive longitudinal data -- Multilevel latent variable model -- Occupational stress -- Realtime assessment -- Simultaneous equation model; Social sciences -- Statistical methods -- Periodicals; Statistics -- Periodicals; 300.15195
• DOI: 10.1111/rssa.12191
• Languages: English
• ISSNs: 0964-1998

Abstract

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.