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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, Fiona, Clarke, Paul, Leckie, George, Allan, Julia and Johnston, Derek (2016) 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 . ISSN 1467-985X

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Abstract

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
Official URL: http://onlinelibrary.wiley.com/journal/10.1111/(IS...
Additional Information: © 2016 The Authors, Journal of the Royal Statistical Society: Series A
Library of Congress subject classification: H Social Sciences > HA Statistics
Sets: Departments > Statistics
Project and Funder Information:
Project IDFunder NameFunder ID
CZH/4/394Chief Scientist OfficeUNSPECIFIED
ES-576-25-0032Economic and Social Research Councilhttp://dx.doi.org/10.13039/501100000269
Projects: CZH/4/394; RES-576-25-0032
Funders: Chief Scientist Office, Economic and Social Research Council
Date Deposited: 08 Jan 2016 15:54
URL: http://eprints.lse.ac.uk/64893/

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