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

Fiona Steele*, Paul S Clarke, George Leckie, Julia Allan, Derek Johnston

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

6 Citations (Scopus)
281 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)263-283
Number of pages21
JournalJournal of the Royal Statistical Society: Series A
Volume180
Issue number1
Early online date10 Mar 2016
DOIs
Publication statusPublished - Jan 2017

Keywords

  • Ecological momentary assessment
  • Simultaneous equation model
  • Realtime assessment
  • Occupational stress
  • Multilevel latent variable model
  • Intensive longitudinal data
  • High frequency data

Fingerprint Dive into the research topics of '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'. Together they form a unique fingerprint.

  • Lemma 3

    Rintoul, D. A.

    1/10/1130/09/14

    Project: Research

Cite this