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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

Steele, F and Clarke, P and Leckie, G and Allan, J and Johnston, D (2017) '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.' Journal of the Royal Statistical Society. Series A: Statistics in Society, 180 (1). 263 - 283. ISSN 0964-1998

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Abstract

© 2016 Royal Statistical Society 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.

Item Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
R Medicine > RT Nursing
Divisions: Faculty of Social Sciences > Institute for Social and Economic Research
Depositing User: Jim Jamieson
Date Deposited: 19 Nov 2016 16:05
Last Modified: 04 Feb 2019 11:16
URI: http://repository.essex.ac.uk/id/eprint/18050

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