Twelve frequently asked questions about growth curve modeling
Open accessAbstract
Longitudinal data analysis has long played a significant role in empirical research within the developmental sciences. The past decade has given rise to a host of new and exciting analytic methods for studying between-person differences in within-person change. These methods are broadly organized under the term growth curve models. The historical lines of development leading to current growth models span multiple disciplines within both the social and statistical sciences, and this in turn makes it challenging for developmental researchers to gain a broader understanding of the current state of this literature. To help address this challenge, the authors pose 12 questions that frequently arise in growth curve modeling, particularly in applications within developmental psychology. They provide concise and nontechnical responses to each question and make specific recommendations for further readings.
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Individual baseline differences were considered by random intercepts, while random slopes captured differences in individual trajectories over time.
“Individual baseline differences were considered by random intercepts, while random slopes capture differences in individual trajectories over time (61).”
From Reducing neuroendocrine psychosocial stress response through socio-emotional dyadic but not mindfulness online training (2024) · cites this paper as [61]
The sample size was quite small; for growth models, a sample size of at least 100 is preferred, but models with much smaller sample sizes have been fitted successfully.
“First, although our RCT has one of the biggest samples within PTSD trials on young patients, our sample size was quite small. For growth models, a sample size of at least 100 is preferred, but also models with much smaller sample sizes have been fitted successfully [59].”
From Get secure soon: attachment in abused adolescents and young adults before and after trauma-focused cognitive processing therapy. (2021) · cites this paper as [59]
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- Authors
- Curran, P. J., Obeidat, K., & Losardo, D.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Curran, Patrick J.
- ORCID
- Curran, Patrick J.
- Venue
- Journal of Cognition and Development
- Publisher
- Informa UK Limited
- Published
- 2010-04-30
- Volume
- 11
- Issue
- 2
- Pages
- 121-136
- ISSN
- 1524-8372 (ISSN-L)
- 1532-7647
- PMC
- PMC3131138
- OpenAlex
- W2079875205
- Cited by
- 1,246
- References
- 75
- Citations by year
- 2026: 83 · 2025: 98 · 2024: 143 · 2023: 102 · 2022: 97 · 2021: 126 · 2020: 112 · 2019: 124 · 2018: 101 · 2017: 89 · 2016: 65 · 2015: 40 · 2014: 26 · 2013: 23 · 2012: 11
- FWCI
- 10.10
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Cognition and Development (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Institute on Drug Abuse (R01DA015398)
- 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
- growth curve models, longitudinal analysis, developmental psychology, between-person differences, within-person change, developmental trajectories
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