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Optimal time lags in panel studies.
Abstract
Cross-lagged regression coefficients are frequently used to test hypotheses in panel designs. However, these coefficients have particular properties making them difficult to interpret. In particular, cross-lagged regression coefficients may vary, depending on the respective time lags between different sets of measurement occasions. This article introduces the concept of an optimal time lag. Further, it is demonstrated that optimal time lags in panel studies are related to the stabilities of the variables investigated, and that in unidirectional systems, they may be unrelated to the size of possible true effects. The results presented also suggest that optimal time lags for panel designs are usually quite short. Implications are (a) that interpreting cross-lagged regression coefficients requires taking the time lag between measurement occasions into account, and (b) that in much research, far shorter time lags than those frequently found in the literature are justifiable, and we call for more "shortitudinal" studies in the future.
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“Nonetheless, Dormann and Griffin [77] recommend using shorter time lags of less than one year, even with high stabilities, because of other influential factors, such as unmeasured third variables.”
From Procrastination, depression and anxiety symptoms in university students: a three-wave longitudinal study on the mediating role of perceived stress (2024) · cites this paper as [77]
In the citing paper
“The choice of the measurement interval was guided by the principle that time lags in panel studies should correspond to the expected speed of the underlying processes”
From Algorithmic short-video music consumption and academic related functions: a three-wave longitudinal study of university students (2026) · cites this paper as Dormann and Griffin, 2015
In the citing paper
“As the outcomes of these longitudinal models depend largely on the time-interval between observations41,42, the annual nature of the data needs to be considered.”
From Windows of developmental sensitivity to social media (2022) · cites this paper as [42]
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“Such research would need to use a research design with repeated short-term assessments as well as repeated long-term assessments (measurement-burst designs; see Dormann & Griffin, 2015; Sliwinski, 2008).”
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Metadata
- Authors
- Dormann, C., & Griffin, M. A.
- Affiliations
- Johannes Gutenberg University Mainz (DE)
- The University of Western Australia (AU)
- Venue
- Psychological Methods
- Published
- 2015
- Volume
- 20
- Issue
- 4
- Pages
- 489-505
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2411399476
- Cited by
- 856
- References
- 51
- Citations by year
- 2026: 176 · 2025: 134 · 2024: 113 · 2023: 88 · 2022: 86 · 2021: 79 · 2020: 50 · 2019: 51 · 2018: 33 · 2017: 23 · 2016: 18 · 2015: 3
- FWCI
- 22.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Methods (publishedVersion)
- PubMed (publishedVersion)
- UniSA Research Outputs Repository (University of South Australia) (acceptedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- eSpace (Curtin University) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- panel survey
- MeSH terms
- Child, Depression, Humans, Longitudinal Studies, Regression Analysis, Research Design, Time Factors, Models, Statistical
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