The DOI matches its Crossref record.
Group-Based Modeling of Development
Abstract
This book provides a systematic exposition of a group-based statistical method for analyzing longitudinal data in the social and behavioral sciences and in medicine. The methods can be applied to a wide range of data, such as that describing the progression of delinquency and criminality over the life course, or changes in income over time.
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In the citing paper
“The mean a posteriori probability of being assigned to high- and low-risk groups was above the recommended .7 threshold (females: high risk M = .86, low risk M = .85; males: high risk M = .80, low risk M = .91), suggesting that hard classification into high and low groups can be confidently used as an exposure variable (Nagin, 2005).”
From Pathways of association between disordered eating in adolescence and mental health outcomes in young adulthood during the COVID-19 pandemic (2023) · cites this paper as Nagin, 2005
In the citing paper
“The odds of correct classification were also examined for each model specification to guide final model selection (Nagin, 2005;Wheeler, 2016).”
From An Officer-Level Examination of the Prevalence and Correlates of Police Body-Worn Camera Activation (2025) · cites this paper as Nagin, 2005
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Items 1,001–1,016 of 1,016
Prinz, N., Schwandt, A., Becker, M., Denzer, C., Flury, M., Fritsch, M., Galler, A., Lemmer, A., Papsch, M., Reinehr, T., et al. (2018) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2018.05.014 · Cited by 32
Yoon, S. (2018) · Journal of Child and Family Studies · doi:10.1007/s10826-017-0904-4 · Cited by 31
The Four U’s: Latent Classes of Hookup Motivations among College Students
Uecker, J. E., Pearce, L. D., & Andercheck, B. (2015) · Social Currents · doi:10.1177/2329496515579761 · Cited by 30
Smith, K. E., Mason, T. B., Cao, L., Crosby, R. D., Steffen, K. J., Garcia, L., King, W. C., & Mitchell, J. E. (2020) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2020.08.007 · Cited by 31
Kinnunen, S. M., Puolakanaho, A., Tolvanen, A., Mäkikangas, A., & Lappalainen, R. (2019) · International Journal of Stress Management · doi:10.1037/str0000095 · Cited by 28
Predictors of Future Cognitive Decline in Persons with Mild Cognitive Impairment
Xie, H., Mayo, N., & Koski, L. (2011) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000334996 · Cited by 26
Verschueren, M., Claes, L., Palmeroni, N., Bogaerts, A., Gandhi, A., Moons, P., & Luyckx, K. (2020) · Journal of Youth and Adolescence · doi:10.1007/s10964-019-01174-0 · Cited by 26
Bommarito, P. A., Cantonwine, D. E., Stevens, D. R., Welch, B. M., Davalos, A. D., Zhao, S., McElrath, T. F., & Ferguson, K. K. (2023) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2022.10.006 · Cited by 24
Yao, J., Wang, H., Yan, J., Shao, D., Sun, Q., & Yin, X. (2021) · Patient Preference and Adherence · doi:10.2147/ppa.s292086 · Cited by 18
Gender differences in the trajectories and the risk factors of depressive symptoms in later life
Lee, J., Jang, S.-N., & Cho, S.-I. (2017) · International Psychogeriatrics · doi:10.1017/s1041610217000709 · Cited by 14
Domènech-Abella, J., Gabarrell-Pascuet, A., García-Mieres, H., Mortier, P., Felez-Nobrega, M., Cristóbal-Narváez, P., Vilagut, G., Olaya, B., Alonso, J., & Haro, J. M. (2023) · Psychiatry Research · doi:10.1016/j.psychres.2023.115327 · Cited by 10
Young, C. A., Mills, R., Langdon, D., Sharrack, B., Majeed, T., Kalra, S., Footitt, D., Rog, D., Harrower, T., Nicholas, R., et al. (2022) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2022.120188 · Cited by 10
An Officer-Level Examination of the Prevalence and Correlates of Police Body-Worn Camera Activation
Huff, J., White, M. D., Malm, A. E., & Katz, C. M. (2025) · Police Quarterly · doi:10.1177/10986111241241751 · Cited by 9
“A combination of statistical criteria (e.g., the Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC)) and visual inspections of various models are used to identify the optimal model (Nagin, 2005).”
Loose, T., Geoffroy, M. C., Orri, M., Chadi, N., Scardera, S., Booij, L., Breton, E., Tremblay, R., Boivin, M., & Coté, S. (2023) · Canadian Journal of Public Health · doi:10.17269/s41997-022-00715-8 · Cited by 7
“…being assigned to high- and low-risk groups was above the recommended .7 threshold (females: high risk M = .86, low risk M = .85; males: high risk M = .80, low risk M = .91), suggesting that hard classification into high and low groups can be confidently used as an exposure variable (Nagin, 2005).”
BackgroundGoyal, N., Levine, B. J., Crawford, S. L., & Avis, N. E. (2024) · Journal of Cancer Survivorship · doi:10.1007/s11764-022-01247-3 · Cited by 4
“To address our second goal, we used group-based trajectory modeling [28] of sleep disturbance scores over the above-described 10-year time period in BCS.”
Trajectory of maternal depression and parasomnias
Guttier, M. C., Halal, C. S., Matijasevich, A., Del‐Ponte, B., Tovo‐Rodrigues, L., Barros, F., Bassani, D. G., & Santos, I. S. (2024) · Journal of Sleep Research · doi:10.1111/jsr.13870 · Cited by 1
“A polynomial function is used to model the relationship between an attribute (i.e., maternal depression) and age or time (Nagin, 2005; Nagin & Odgers, 2010; Nagin & Tremblay, 1999).”
MethodInfluential
Metadata
- Authors
- NAGIN, D.
- Corresponding author
- NAGIN, Daniel
- ORCID
- NAGIN, Daniel
- Venue
- Harvard University Press eBooks
- Publisher
- Harvard University Press
- Published
- 2005-01-01
- OpenAlex
- W1598612182
- Cited by
- 4,164
- References
- 0
- Citations by year
- 2026: 234 · 2025: 288 · 2024: 271 · 2023: 264 · 2022: 297 · 2021: 323 · 2020: 263 · 2019: 270 · 2018: 225 · 2017: 220 · 2016: 222 · 2015: 241 · 2014: 155 · 2013: 154 · 2012: 176
- FWCI
- 19.40
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Harvard University Press eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- longitudinal analysis, life course, delinquency, criminality, income change, developmental trajectories
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