On the power of multivariate latent growth curve models to detect correlated change.
Open accessAbstract
We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris (1985) were used to evaluate the power to detect slope covariances. Even with large samples (N = 500) and several longitudinal occasions (4 or 5), statistical power to detect covariance of slopes was moderate to low unless growth curve reliability at study onset was above .90. Studies using LGCMs may fail to detect slope correlations because of low power rather than a lack of relationship of change between variables. The present findings allow researchers to make more informed design decisions when planning a longitudinal study and aid in interpreting LGCM results regarding correlated interindividual differences in rates of development.
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Hertzog et al. showed that power to detect individual differences in change is dramatically affected by growth-curve reliability, which is influenced by measurement reliability.
“Hertzog et al. (2006) showed that power to detect individual differences in change is dramatically affected by growth-curve reliability, which in turn is influenced by measurement reliability.”
From Enrichment Effects on Adult Cognitive Development: Can the Functional Capacity of Older Adults Be Preserved and Enhanced? (2008) · cites this paper as Hertzog, Lindenberger, Ghisletta, & von Oertzen, 2006
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- Authors
- Hertzog, C., Lindenberger, U., Ghisletta, P., & von Oertzen, T.
- Affiliations
- University of Geneva (CH)
- Venue
- Psychological Methods
- Published
- 2006
- Volume
- 11
- Issue
- 3
- Pages
- 244-252
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2170742243
- Cited by
- 174
- References
- 4
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 7 · 2023: 6 · 2022: 6 · 2021: 8 · 2020: 7 · 2019: 5 · 2018: 15 · 2017: 10 · 2016: 9 · 2015: 11 · 2014: 12 · 2013: 10 · 2012: 8
- FWCI
- 7.82
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- Locations
- Psychological Methods (publishedVersion)
- PubMed (publishedVersion)
- Archive ouverte UNIGE (University of Geneva) (publishedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
- Funders
- Deutsche Forschungsgemeinschaft
- Georgia Institute of Technology
- 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
- latent growth curve models, statistical power, measurement reliability, measurement error, sample size, longitudinal study design
- MeSH terms
- Aging, Humans, Models, Psychological, Psychology, Multivariate Analysis, Area Under Curve
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