The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm
Open accessAbstract
The R package lcmm provides a series of functions to estimate statistical models based on linear mixed model theory. It includes the estimation of mixed models and latent class mixed models for Gaussian longitudinal outcomes (hlme), curvilinear and ordinal univariate longitudinal outcomes (lcmm) and curvilinear multivariate outcomes (multlcmm), as well as joint latent class mixed models (Jointlcmm) for a (Gaussian or curvilinear) longitudinal outcome and a time-to-event outcome that can be possibly left-truncated right-censored and defined in a competing setting. Maximum likelihood esimators are obtained using a modified Marquardt algorithm with strict convergence criteria based on the parameters and likelihood stability, and on the negativity of the second derivatives. The package also provides various post-fit functions including goodness-of-fit analyses, classification, plots, predicted trajectories, individual dynamic prediction of the event and predictive accuracy assessment. This paper constitutes a companion paper to the package by introducing each family of models, the estimation technique, some implementation details and giving examples through a dataset on cognitive aging.
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Cites
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Cited by
The GRoLTS-Checklist: Guidelines for Reporting on Latent Trajectory Studies
van de Schoot, R., Sijbrandij, M., Winter, S. D., Depaoli, S., & Vermunt, J. K. (2017) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705511.2016.1247646 · Cited by 721
Biomarker Changes during 20 Years Preceding Alzheimer’s Disease
Jia, J., Ning, Y., Chen, M., Wang, S., Yang, H., Li, F., Ding, J., Li, Y., Zhao, B., Lyu, J., et al. (2024) · New England Journal of Medicine · doi:10.1056/nejmoa2310168 · Cited by 455
Framework to construct and interpret latent class trajectory modelling
Lennon, H., Kelly, S., Sperrin, M., Buchan, I., Cross, A. J., Leitzmann, M., Cook, M. B., & Renehan, A. G. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-020683 · Cited by 419
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Vistisen, D., Andersen, G. S., Hulman, A., Persson, F., Rossing, P., & Jørgensen, M. E. (2019) · Diabetes Care · doi:10.2337/dc19-0349 · Cited by 167
Metadata
- Authors
- Proust-Lima, C., Philipps, V., & Liquet, B.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2017
- Volume
- 78
- Issue
- 2
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W1480271113
- Cited by
- 1,106
- References
- 38
- FWCI
- 38.26
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Proust-Lima, C., Philipps, V., & Liquet, B. (2017). Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm. Journal of Statistical Software. https://doi.org/10.18637/jss.v078.i02
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