The DOI matches its Crossref record; 106 of the 106 references it cites were found in a registry or an index.
Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches
Open accessAbstract
Trajectory modelling techniques have been developed to determine subgroups within a given population and are increasingly used to better understand intra- and inter-individual variability in health outcome patterns over time. The objectives of this narrative review are to explore various trajectory modelling approaches useful to epidemiological research and give an overview of their applications and differences. Guidance for reporting on the results of trajectory modelling is also covered. Trajectory modelling techniques reviewed include latent class modelling approaches, ie, growth mixture modelling (GMM), group-based trajectory modelling (GBTM), latent class analysis (LCA), and latent transition analysis (LTA). A parallel is drawn to other individual-centered statistical approaches such as cluster analysis (CA) and sequence analysis (SA). Depending on the research question and type of data, a number of approaches can be used for trajectory modelling of health outcomes measured in longitudinal studies. However, the various terms to designate latent class modelling approaches (GMM, GBTM, LTA, LCA) are used inconsistently and often interchangeably in the available scientific literature. Improved consistency in the terminology and reporting guidelines have the potential to increase researchers' efficiency when it comes to choosing the most appropriate technique that best suits their research questions.
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Li, Y., Luk, T. T., Cheung, Y. T. D., Zhao, S., Zeng, Y., Tong, H. S. C., Lai, V. W. Y., & Wang, M. P. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.17796 · Cited by 13
Mousavi, M., Saei Ghare Naz, M., Firouzi, F., Azizi, F., & Ramezani Tehrani, F. (2024) · BMC Public Health · doi:10.1186/s12889-024-19996-4 · Cited by 7
Wang, J., Zhang, W., Song, P., Wang, T., Yao, Y., Chen, Y., Lin, H., Yang, X., Chen, X., & Fu, C. (2024) · Psychology Research and Behavior Management · doi:10.2147/prbm.s484113 · Cited by 6
Metadata
- Authors
- Nguena Nguefack, H. L., Pagé, M. G., Katz, J., Choinière, M., Vanasse, A., Dorais, M., Samb, O. M., & Lacasse, A.
- Venue
- Clinical Epidemiology
- Publisher
- Informa UK Limited
- Published
- 2020-10
- Volume
- Volume 12
- Pages
- 1205-1222
- ISSN
- 1179-1349 (ISSN-L)
- OpenAlex
- W3094699016
- Cited by
- 527
- References
- 106
- FWCI
- 9.55
- Type
- journal article
- Language
- en
- Open access
- gold
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- Nguena Nguefack, H. L., Pagé, M. G., Katz, J., Choinière, M., Vanasse, A., Dorais, M., Samb, O. M., & Lacasse, A. (2020). Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches. Clinical Epidemiology. https://doi.org/10.2147/clep.s265287
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