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A graphical vector autoregressive modelling approach to the analysis of electronic diary data
Open accessAbstract
BACKGROUND: In recent years, electronic diaries are increasingly used in medical research and practice to investigate patients' processes and fluctuations in symptoms over time. To model dynamic dependence structures and feedback mechanisms between symptom-relevant variables, a multivariate time series method has to be applied. METHODS: We propose to analyse the temporal interrelationships among the variables by a structural modelling approach based on graphical vector autoregressive (VAR) models. We give a comprehensive description of the underlying concepts and explain how the dependence structure can be recovered from electronic diary data by a search over suitable constrained (graphical) VAR models. RESULTS: The graphical VAR approach is applied to the electronic diary data of 35 obese patients with and without binge eating disorder (BED). The dynamic relationships for the two subgroups between eating behaviour, depression, anxiety and eating control are visualized in two path diagrams. Results show that the two subgroups of obese patients with and without BED are distinguishable by the temporal patterns which influence their respective eating behaviours. CONCLUSION: The use of the graphical VAR approach for the analysis of electronic diary data leads to a deeper insight into patient's dynamics and dependence structures. An increasing use of this modelling approach could lead to a better understanding of complex psychological and physiological mechanisms in different areas of medical care and research.
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“The temporal dynamics between two or more variables may be investigated using vector auto-regression (VAR) models. This way complex relationships between variables can be unraveled, such that it becomes possible to make inferences about person-level cause -effect relationships (Wild et al., 2010).”
From Mood Disorders in Everyday Life: A Systematic Review of Experience Sampling and Ecological Momentary Assessment Studies (2012) · cites this paper as Wild et al., 2010
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Metadata
- Authors
- Wild, B., Eichler, M., Friederich, H.-C., Hartmann, M., Zipfel, S., & Herzog, W.
- Affiliations
- University Hospital Heidelberg (DE)
- Maastricht University (NL)
- Universitätsklinikum Tübingen (DE)
- Corresponding author
- Wild, Beate
- Eichler, Michael
- ORCID
- Venue
- BMC Medical Research Methodology
- Published
- 2010-04-01
- Volume
- 10
- Issue
- 1
- Pages
- 28-28
- ISSN
- 1471-2288 (ISSN-L)
- PMC
- PMC2869334
- OpenAlex
- W2028782034
- Cited by
- 123
- References
- 54
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 7 · 2023: 10 · 2022: 12 · 2021: 18 · 2020: 22 · 2019: 6 · 2018: 13 · 2017: 2 · 2016: 8 · 2015: 3 · 2014: 4 · 2013: 1 · 2012: 3
- FWCI
- 1.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Research Methodology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
- Keywords
- electronic diary, multivariate time series, binge eating disorder, obesity, eating behaviour, depression, anxiety, food intake regulation, path diagrams
- MeSH terms
- Adult, Anxiety, Computer Graphics, Depression, Female, Humans, Male, Models, Theoretical, Obesity, Regression Analysis, Multivariate Analysis, Computers, Handheld, Young Adult, Binge-Eating Disorder
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